Patent Publication Number: US-9411584-B2

Title: Methods, apparatus, instructions, and logic to provide vector address conflict detection functionality

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     This application is related to: application Ser. No. 12/079,774, titled “Vector Instructions to Enable Efficient Synchronization and Parallel Reduction Operations,” filed Oct. 1, 2009; application Ser. No. 12/974,157, titled “Mechanism for Conflict Detection Using SIMD,” filed Dec. 21, 2010; and application Ser. No. 12/976,616, titled “Vector Conflict Instructions,” filed Dec. 22, 2010. 
     FIELD OF THE DISCLOSURE 
     The present disclosure pertains to the field of processing logic, microprocessors, and associated instruction set architecture that, when executed by the processor or other processing logic, perform logical, mathematical, or other functional operations. In particular, the disclosure relates to instructions and logic to provide SIMD vector address conflict detection functionality. 
     BACKGROUND OF THE DISCLOSURE 
     Modern processors often include instructions to provide operations that are computationally intensive, but offer a high level of data parallelism that can be exploited through an efficient implementation using various data storage devices, such as for example, single-instruction multiple-data (SIMD) vector registers. In SIMD execution, a single instruction operates on multiple data elements concurrently or simultaneously. This is typically implemented by extending the width of various resources such as registers and arithmetic logic units (ALUs), allowing them to hold or operate on multiple data elements, respectively. 
     The central processing unit (CPU) may provide such parallel hardware to support the SIMD processing of vectors. A vector is a data structure that holds a number of consecutive data elements. A vector register of size L may contain N vector elements of size M, where N=L/M. For instance, a 64-byte vector register may be partitioned into (a) 64 vector elements, with each element holding a data item that occupies 1 byte, (b) 32 vector elements to hold data items that occupy 2 bytes (or one “word”) each, (c) 16 vector elements to hold data items that occupy 4 bytes (or one “doubleword”) each, or (d) 8 vector elements to hold data items that occupy 8 bytes (or one “quadword”) each. 
     A number of applications have large amounts of data-level parallelism and may be able to benefit from SIMD support. However, some applications spend a significant amount of time in operations on a set of sparse locations. Moreover, sometimes sequential operations are performed on the same sparse locations and so these applications may see only limited benefit from SIMD, operations. To maintain SIMD efficiency, some architectures allow not only SIMD arithmetic operations but also SIMD memory reads and writes (through gather and scatter operations). Scatter reductions are common operations in many applications. For example, a scatter-add operation can be used to enable multiple values of a first array to be reduced into (i.e., added to) selected elements of a second array according to a distribution of indices, which can often be random. But because of this, it may be difficult to efficiently process multiple elements concurrently (i.e., in SIMD mode). One concern is to ensure that scalar program order is preserved when necessary. Another concern is to ensure that when data is scattered into memory, the resulting vector of memory addresses includes only unique addresses (i.e., there are no duplicate addresses). 
     For example, histogram calculations are common operations in many image processing applications. A histogram may be used to track the distribution of color values of pixels in an image. However, updates to the histogram array may be random, depending on input data to an array. In particular, indices of neighboring elements may point to the same histogram bin. Accordingly, conflict detection and resolution is required to detect multiple dependent updates to the same locations and to ensure that scalar program order is preserved. This is precisely the kind of condition that can make it very difficult to process multiple data concurrently or simultaneously (i.e., using SIMD operations). 
     To date, potential solutions to such conflict concerns and related processing difficulties have not been adequately explored. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The present invention is illustrated by way of example and not limitation in the figures of the accompanying drawings. 
         FIG. 1A  is a block diagram of one embodiment of a system that executes instructions to provide SIMD address conflict detection functionality. 
         FIG. 1B  is a block diagram of another embodiment of a system that executes instructions to provide SIMD address conflict detection functionality. 
         FIG. 1C  is a block diagram of another embodiment of a system that executes instructions to provide SIMD address conflict detection functionality. 
         FIG. 2  is a block diagram of one embodiment of a processor that executes instructions to provide SIMD address conflict detection functionality. 
         FIG. 3A  illustrates packed data types according to one embodiment. 
         FIG. 3B  illustrates packed data types according to one embodiment. 
         FIG. 3C  illustrates packed data types according to one embodiment. 
         FIG. 3D  illustrates an instruction encoding to provide SIMD address conflict detection functionality according to one embodiment. 
         FIG. 3E  illustrates an instruction encoding to provide SIMD address conflict detection functionality according to another embodiment. 
         FIG. 3F  illustrates an instruction encoding to provide SIMD address conflict detection functionality according to another embodiment. 
         FIG. 3G  illustrates an instruction encoding to provide SIMD address conflict detection functionality according to another embodiment. 
         FIG. 3H  illustrates an instruction encoding to provide SIMD address conflict detection functionality according to another embodiment. 
         FIG. 4A  illustrates elements of one embodiment of a processor micro-architecture to execute instructions that provide SIMD address conflict detection functionality. 
         FIG. 4B  illustrates elements of another embodiment of a processor micro-architecture to execute instructions that provide SIMD address conflict detection functionality. 
         FIG. 5  is a block diagram of one embodiment of a processor to execute instructions that provide SIMD address conflict detection functionality. 
         FIG. 6  is a block diagram of one embodiment of a computer system to execute instructions that provide SIMD address conflict detection functionality. 
         FIG. 7  is a block diagram of another embodiment of a computer system to execute instructions that provide SIMD address conflict detection functionality. 
         FIG. 8  is a block diagram of another embodiment of a computer system to execute instructions that provide SIMD address conflict detection functionality. 
         FIG. 9  is a block diagram of one embodiment of a system-on-a-chip to execute instructions that provide SIMD address conflict detection functionality. 
         FIG. 10  is a block diagram of an embodiment of a processor to execute instructions that provide SIMD address conflict detection functionality. 
         FIG. 11  is a block diagram of one embodiment of an IP core development system that provides SIMD address conflict detection functionality. 
         FIG. 12  illustrates one embodiment of an architecture emulation system that provides SIMD address conflict detection functionality. 
         FIG. 13  illustrates one embodiment of a system to translate instructions that provide SIMD address conflict detection functionality. 
         FIG. 14A  illustrates a flow diagram for one embodiment of an example of using an instruction to provide SIMD vector leading zero count functionality useful for generating permute controls for efficient vector address conflict resolution. 
         FIG. 14B  illustrates a flow diagram for one embodiment of an example of using an instruction to provide SIMD vector address conflict detection functionality. 
         FIG. 14C  illustrates a flow diagram for one embodiment of an example of using an instruction to provide SIMD vector address conflict resolution with vector population count functionality. 
         FIG. 14D  illustrates a flow diagram for an alternative embodiment of an example of using combined instructions to provide efficient SIMD vector address conflict resolution. 
         FIG. 15A  illustrates a flow diagram for one embodiment of a process to provide SIMD permute controls with vector leading zero count functionality. 
         FIG. 15B  illustrates a flow diagram for one embodiment of a process to provide SIMD vector address conflict detection functionality. 
         FIG. 15C  illustrates a flow diagram for one embodiment of a process to provide SIMD vector address conflict resolution with vector population count functionality. 
         FIG. 15D  illustrates a flow diagram for an alternative embodiment of a combined process to provide efficient SIMD vector address conflict resolution. 
         FIG. 16  illustrates an embodiment of an apparatus for executing an instruction to provide SIMD vector leading zero count functionality useful for generating permute controls for efficient vector address conflict resolution. 
         FIG. 17  illustrates an embodiment of an apparatus for executing an instruction to provide SIMD vector address conflict detection functionality for efficient vector address conflict resolution. 
         FIG. 18  illustrates an embodiment of an apparatus for executing an instruction to provide SIMD vector population count functionality for efficient vector address conflict resolution. 
     
    
    
     DETAILED DESCRIPTION 
     The following description discloses instructions and processing logic to provide SIMD address conflict detection functionality within or in association with a processor, computer system, or other processing apparatus. Instructions and logic are disclosed herein to provide SIMD address conflict detection functionality. Some embodiments include processors with a register with a variable plurality of data fields, each of the data fields to store an offset for a data element in a memory. A destination register has corresponding data fields, each of these data fields to store a variable second plurality of bits to store a conflict mask having a mask bit for each offset. Responsive to decoding a vector conflict instruction, execution units compare the offset in each data field with every less significant data field to determine if they hold a matching offset, and in corresponding conflict masks in the destination register, set any mask bits corresponding to a less significant data field with a matching offset. Vector address conflict detection can be used with variable sized elements and to generate conflict masks to resolve dependencies in gather-modify-scatter SIMD operations. 
     The following description discloses a number of instructions, methods and processing logic to resolve dependencies in gather-modify-scatter SIMD operations. It will be appreciated that SIMD vector conflict instructions, as in the embodiments described herein, may be used for variable sized elements and memory offsets to provide SIMD vector address conflict detection functionality and to generate conflict masks for efficient SIMD address conflict resolution. It will also be appreciated that SIMD vector leading zero count instructions, as in the embodiments described herein, may be used with variable sized elements and conflict masks to provide SIMD permute controls, which will be described in greater detail below, thereby permitting more efficient SIMD address conflict resolution in registers without performing dependent computations through memory. It will further be appreciated that SIMD vector population count instructions, as in the embodiments described herein, may be used with variable sized elements and conflict masks to efficiently compute iteration counts and to provide SIMD completion masks for each iteration of a SIMD address conflict resolution, which will be described in greater detail below. Thus the instructions and logic disclosed herein provide for more efficient SIMD address conflict resolution especially in gather-modify-scatter applications. 
     In the following description, numerous specific details such as processing logic, processor types, micro-architectural conditions, events, enablement mechanisms, and the like are set forth in order to provide a more thorough understanding of embodiments of the present invention. It will be appreciated, however, by one skilled in the art that the invention may be practiced without such specific details. Additionally, some well known structures, circuits, and the like have not been shown in detail to avoid unnecessarily obscuring embodiments of the present invention. 
     Although the following embodiments are described with reference to a processor, other embodiments are applicable to other types of integrated circuits and logic devices. Similar techniques and teachings of embodiments of the present invention can be applied to other types of circuits or semiconductor devices that can benefit from higher pipeline throughput and improved performance. The teachings of embodiments of the present invention are applicable to any processor or machine that performs data manipulations. However, the present invention is not limited to processors or machines that perform 512 bit, 256 bit, 128 bit, 64 bit, 32 bit, or 16 bit data operations and can be applied to any processor and machine in which manipulation or management of data is performed. In addition, the following description provides examples, and the accompanying drawings show various examples for the purposes of illustration. However, these examples should not be construed in a limiting sense as they are merely intended to provide examples of embodiments of the present invention rather than to provide an exhaustive list of all possible implementations of embodiments of the present invention. 
     Although the below examples describe instruction handling and distribution in the context of execution units and logic circuits, other embodiments of the present invention can be accomplished by way of data and/or instructions stored on a machine-readable, tangible medium, which when performed by a machine cause the machine to perform functions consistent with at least one embodiment of the invention. In one embodiment, functions associated with embodiments of the present invention are embodied in machine-executable instructions. The instructions can be used to cause a general-purpose or special-purpose processor that is programmed with the instructions to perform the steps of the present invention. Embodiments of the present invention may be provided as a computer program product or software which may include a machine or computer-readable medium having stored thereon instructions which may be used to program a computer (or other electronic devices) to perform one or more operations according to embodiments of the present invention. Alternatively, steps of embodiments of the present invention might be performed by specific hardware components that contain fixed-function logic for performing the steps, or by any combination of programmed computer components and fixed-function hardware components. 
     Instructions used to program logic to perform embodiments of the invention can be stored within a memory in the system, such as DRAM, cache, flash memory, or other storage. Furthermore, the instructions can be distributed via a network or by way of other computer readable media. Thus a machine-readable medium may include any mechanism for storing or transmitting information in a form readable by a machine (e.g., a computer), but is not limited to, floppy diskettes, optical disks, Compact Disc, Read-Only Memory (CD-ROMs), and magneto-optical disks, Read-Only Memory (ROMs), Random Access Memory (RAM), Erasable Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), magnetic or optical cards, flash memory, or a tangible, machine-readable storage used in the transmission of information over the Internet via electrical, optical, acoustical or other forms of propagated signals (e.g., carrier waves, infrared signals, digital signals, etc.). Accordingly, the computer-readable medium includes any type of tangible machine-readable medium suitable for storing or transmitting electronic instructions or information in a form readable by a machine (e.g., a computer). 
     A design may go through various stages, from creation to simulation to fabrication. Data representing a design may represent the design in a number of manners. First, as is useful in simulations, the hardware may be represented using a hardware description language or another functional description language. Additionally, a circuit level model with logic and/or transistor gates may be produced at some stages of the design process. Furthermore, most designs, at some stage, reach a level of data representing the physical placement of various devices in the hardware model. In the case where conventional semiconductor fabrication techniques are used, the data representing the hardware model may be the data specifying the presence or absence of various features on different mask layers for masks used to produce the integrated circuit. In any representation of the design, the data may be stored in any form of a machine readable medium. A memory or a magnetic or optical storage such as a disc may be the machine readable medium to store information transmitted via optical or electrical wave modulated or otherwise generated to transmit such information. When an electrical carrier wave indicating or carrying the code or design is transmitted, to the extent that copying, buffering, or re-transmission of the electrical signal is performed, a new copy is made. Thus, a communication provider or a network provider may store on a tangible, machine-readable medium, at least temporarily, an article, such as information encoded into a carrier wave, embodying techniques of embodiments of the present invention. 
     In modern processors, a number of different execution units are used to process and execute a variety of code and instructions. Not all instructions are created equal as some are quicker to complete while others can take a number of clock cycles to complete. The faster the throughput of instructions, the better the overall performance of the processor. Thus it would be advantageous to have as many instructions execute as fast as possible. However, there are certain instructions that have greater complexity and require more in terms of execution time and processor resources. For example, there are floating point instructions, load/store operations, data moves, etc. 
     As more computer systems are used in internet, text, and multimedia applications, additional processor support has been introduced over time. In one embodiment, an instruction set may be associated with one or more computer architectures, including data types, instructions, register architecture, addressing modes, memory architecture, interrupt and exception handling, and external input and output (I/O). 
     In one embodiment, the instruction set architecture (ISA) may be implemented by one or more micro-architectures, which includes processor logic and circuits used to implement one or more instruction sets. Accordingly, processors with different micro-architectures can share at least a portion of a common instruction set. For example, Intel® Pentium 4 processors, Intel® Core™ processors, and processors from Advanced Micro Devices, Inc. of Sunnyvale Calif. implement nearly identical versions of the x86 instruction set (with some extensions that have been added with newer versions), but have different internal designs. Similarly, processors designed by other processor development companies, such as ARM Holdings, Ltd., MIPS, or their licensees or adopters, may share at least a portion a common instruction set, but may include different processor designs. For example, the same register architecture of the ISA may be implemented in different ways in different micro-architectures using new or well-known techniques, including dedicated physical registers, one or more dynamically allocated physical registers using a register renaming mechanism (e.g., the use of a Register Alias Table (RAT), a Reorder Buffer (ROB) and a retirement register file. In one embodiment, registers may include one or more registers, register architectures, register files, or other register sets that may or may not be addressable by a software programmer. 
     In one embodiment, an instruction may include one or more instruction formats. In one embodiment, an instruction format may indicate various fields (number of bits, location of bits, etc.) to specify, among other things, the operation to be performed and the operand(s) on which that operation is to be performed. Some instruction formats may be further broken defined by instruction templates (or sub formats). For example, the instruction templates of a given instruction format may be defined to have different subsets of the instruction format&#39;s fields and/or defined to have a given field interpreted differently. In one embodiment, an instruction is expressed using an instruction format (and, if defined, in a given one of the instruction templates of that instruction format) and specifies or indicates the operation and the operands upon which the operation will operate. 
     Scientific, financial, auto-vectorized general purpose, RMS (recognition, mining, and synthesis), and visual and multimedia applications (e.g., 2D/3D graphics, image processing, video compression/decompression, voice recognition algorithms and audio manipulation) may require the same operation to be performed on a large number of data items. In one embodiment, Single Instruction Multiple Data (SIMD) refers to a type of instruction that causes a processor to perform an operation on multiple data elements. SIMD technology may be used in processors that can logically divide the bits in a register into a number of fixed-sized or variable-sized data elements, each of which represents a separate value. For example, in one embodiment, the bits in a 64-bit register may be organized as a source operand containing four separate 16-bit data elements, each of which represents a separate 16-bit value. This type of data may be referred to as ‘packed’ data type or ‘vector’ data type, and operands of this data type are referred to as packed data operands or vector operands. In one embodiment, a packed data item or vector may be a sequence of packed data elements stored within a single register, and a packed data operand or a vector operand may a source or destination operand of a SIMD instruction (or ‘packed data instruction’ or a ‘vector instruction’). In one embodiment, a SIMD instruction specifies a single vector operation to be performed on two source vector operands to generate a destination vector operand (also referred to as a result vector operand) of the same or different size, with the same or different number of data elements, and in the same or different data element order. 
     SIMD technology, such as that employed by the Intel® Core™ processors having an instruction set including x86, MMX™, Streaming SIMD Extensions (SSE), SSE2, SSE3, SSE4.1, and SSE4.2 instructions, ARM processors, such as the ARM Cortex® family of processors having an instruction set including the Vector Floating Point (VFP) and/or NEON instructions, and MIPS processors, such as the Loongson family of processors developed by the Institute of Computing Technology (ICT) of the Chinese Academy of Sciences, has enabled a significant improvement in application performance (Core™ and MMX™ are registered trademarks or trademarks of Intel Corporation of Santa Clara, Calif.). 
     In one embodiment, destination and source registers/data are generic terms to represent the source and destination of the corresponding data or operation. In some embodiments, they may be implemented by registers, memory, or other storage areas having other names or functions than those depicted. For example, in one embodiment, “DEST1” may be a temporary storage register or other storage area, whereas “SRC1” and “SRC2” may be a first and second source storage register or other storage area, and so forth. In other embodiments, two or more of the SRC and DEST storage areas may correspond to different data storage elements within the same storage area (e.g., a SIMD register). In one embodiment, one of the source registers may also act as a destination register by, for example, writing back the result of an operation performed on the first and second source data to one of the two source registers serving as a destination registers. 
       FIG. 1A  is a block diagram of an exemplary computer system formed with a processor that includes execution units to execute an instruction in accordance with one embodiment of the present invention. System  100  includes a component, such as a processor  102  to employ execution units including logic to perform algorithms for process data, in accordance with the present invention, such as in the embodiment described herein. System  100  is representative of processing systems based on the PENTIUM® III, PENTIUM® 4, Xeon™, Itanium®, XScale™ and/or StrongARM™ microprocessors available from Intel Corporation of Santa Clara, Calif., although other systems (including PCs having other microprocessors, engineering workstations, set-top boxes and the like) may also be used. In one embodiment, sample system  100  may execute a version of the WINDOWS™ operating system available from Microsoft Corporation of Redmond, Wash., although other operating systems (UNIX and Linux for example), embedded software, and/or graphical user interfaces, may also be used. Thus, embodiments of the present invention are not limited to any specific combination of hardware circuitry and software. 
     Embodiments are not limited to computer systems. Alternative embodiments of the present invention can be used in other devices such as handheld devices and embedded applications. Some examples of handheld devices include cellular phones, Internet Protocol devices, digital cameras, personal digital assistants (PDAs), and handheld PCs. Embedded applications can include a micro controller, a digital signal processor (DSP), system on a chip, network computers (NetPC), set-top boxes, network hubs, wide area network (WAN) switches, or any other system that can perform one or more instructions in accordance with at least one embodiment. 
       FIG. 1A  is a block diagram of a computer system  100  formed with a processor  102  that includes one or more execution units  108  to perform an algorithm to perform at least one instruction in accordance with one embodiment of the present invention. One embodiment may be described in the context of a single processor desktop or server system, but alternative embodiments can be included in a multiprocessor system. System  100  is an example of a ‘hub’ system architecture. The computer system  100  includes a processor  102  to process data signals. The processor  102  can be a complex instruction set computer (CISC) microprocessor, a reduced instruction set computing (RISC) microprocessor, a very long instruction word (VLIW) microprocessor, a processor implementing a combination of instruction sets, or any other processor device, such as a digital signal processor, for example. The processor  102  is coupled to a processor bus  110  that can transmit data signals between the processor  102  and other components in the system  100 . The elements of system  100  perform their conventional functions that are well known to those familiar with the art. 
     In one embodiment, the processor  102  includes a Level 1 (L1) internal cache memory  104 . Depending on the architecture, the processor  102  can have a single internal cache or multiple levels of internal cache. Alternatively, in another embodiment, the cache memory can reside external to the processor  102 . Other embodiments can also include a combination of both internal and external caches depending on the particular implementation and needs. Register file  106  can store different types of data in various registers including integer registers, floating point registers, status registers, and instruction pointer register. 
     Execution unit  108 , including logic to perform integer and floating point operations, also resides in the processor  102 . The processor  102  also includes a microcode (ucode) ROM that stores microcode for certain macroinstructions. For one embodiment, execution unit  108  includes logic to handle a packed instruction set  109 . By including the packed instruction set  109  in the instruction set of a general-purpose processor  102 , along with associated circuitry to execute the instructions, the operations used by many multimedia applications may be performed using packed data in a general-purpose processor  102 . Thus, many multimedia applications can be accelerated and executed more efficiently by using the full width of a processor&#39;s data bus for performing operations on packed data. This can eliminate the need to transfer smaller units of data across the processor&#39;s data bus to perform one or more operations one data element at a time. 
     Alternate embodiments of an execution unit  108  can also be used in micro controllers, embedded processors, graphics devices, DSPs, and other types of logic circuits. System  100  includes a memory  120 . Memory  120  can be a dynamic random access memory (DRAM) device, a static random access memory (SRAM) device, flash memory device, or other memory device. Memory  120  can store instructions and/or data represented by data signals that can be executed by the processor  102 . 
     A system logic chip  116  is coupled to the processor bus  110  and memory  120 . The system logic chip  116  in the illustrated embodiment is a memory controller hub (MCH). The processor  102  can communicate to the MCH  116  via a processor bus  110 . The MCH  116  provides a high bandwidth memory path  118  to memory  120  for instruction and data storage and for storage of graphics commands, data and textures. The MCH  116  is to direct data signals between the processor  102 , memory  120 , and other components in the system  100  and to bridge the data signals between processor bus  110 , memory  120 , and system I/O  122 . In some embodiments, the system logic chip  116  can provide a graphics port for coupling to a graphics controller  112 . The MCH  116  is coupled to memory  120  through a memory interface  118 . The graphics card  112  is coupled to the MCH  116  through an Accelerated Graphics Port (AGP) interconnect  114 . 
     System  100  uses a proprietary hub interface bus  122  to couple the MCH  116  to the I/O controller hub (ICH)  130 . The ICH  130  provides direct connections to some I/O devices via a local I/O bus. The local I/O bus is a high-speed I/O bus for connecting peripherals to the memory  120 , chipset, and processor  102 . Some examples are the audio controller, firmware hub (flash BIOS)  128 , wireless transceiver  126 , data storage  124 , legacy I/O controller containing user input and keyboard interfaces, a serial expansion port such as Universal Serial Bus (USB), and a network controller  134 . The data storage device  124  can comprise a hard disk drive, a floppy disk drive, a CD-ROM device, a flash memory device, or other mass storage device. 
     For another embodiment of a system, an instruction in accordance with one embodiment can be used with a system on a chip. One embodiment of a system on a chip comprises of a processor and a memory. The memory for one such system is a flash memory. The flash memory can be located on the same die as the processor and other system components. Additionally, other logic blocks such as a memory controller or graphics controller can also be located on a system on a chip. 
       FIG. 1B  illustrates a data processing system  140  which implements the principles of one embodiment of the present invention. It will be readily appreciated by one of skill in the art that the embodiments described herein can be used with alternative processing systems without departure from the scope of embodiments of the invention. 
     Computer system  140  comprises a processing core  159  capable of performing at least one instruction in accordance with one embodiment. For one embodiment, processing core  159  represents a processing unit of any type of architecture, including but not limited to a CISC, a RISC or a VLIW type architecture. Processing core  159  may also be suitable for manufacture in one or more process technologies and by being represented on a machine readable media in sufficient detail, may be suitable to facilitate said manufacture. 
     Processing core  159  comprises an execution unit  142 , a set of register file(s)  145 , and a decoder  144 . Processing core  159  also includes additional circuitry (not shown) which is not necessary to the understanding of embodiments of the present invention. Execution unit  142  is used for executing instructions received by processing core  159 . In addition to performing typical processor instructions, execution unit  142  can perform instructions in packed instruction set  143  for performing operations on packed data formats. Packed instruction set  143  includes instructions for performing embodiments of the invention and other packed instructions. Execution unit  142  is coupled to register file  145  by an internal bus. Register file  145  represents a storage area on processing core  159  for storing information, including data. As previously mentioned, it is understood that the storage area used for storing the packed data is not critical. Execution unit  142  is coupled to decoder  144 . Decoder  144  is used for decoding instructions received by processing core  159  into control signals and/or microcode entry points. In response to these control signals and/or microcode entry points, execution unit  142  performs the appropriate operations. In one embodiment, the decoder is used to interpret the opcode of the instruction, which will indicate what operation should be performed on the corresponding data indicated within the instruction. 
     Processing core  159  is coupled with bus  141  for communicating with various other system devices, which may include but are not limited to, for example, synchronous dynamic random access memory (SDRAM) control  146 , static random access memory (SRAM) control  147 , burst flash memory interface  148 , personal computer memory card international association (PCMCIA)/compact flash (CF) card control  149 , liquid crystal display (LCD) control  150 , direct memory access (DMA) controller  151 , and alternative bus master interface  152 . In one embodiment, data processing system  140  may also comprise an I/O bridge  154  for communicating with various I/O devices via an I/O bus  153 . Such I/O devices may include but are not limited to, for example, universal asynchronous receiver/transmitter (UART)  155 , universal serial bus (USB)  156 , Bluetooth wireless UART  157  and I/O expansion interface  158 . 
     One embodiment of data processing system  140  provides for mobile, network and/or wireless communications and a processing core  159  capable of performing SIMD operations including a text string comparison operation. Processing core  159  may be programmed with various audio, video, imaging and communications algorithms including discrete transformations such as a Walsh-Hadamard transform, a fast Fourier transform (FFT), a discrete cosine transform (DCT), and their respective inverse transforms; compression/decompression techniques such as color space transformation, video encode motion estimation or video decode motion compensation; and modulation/demodulation (MODEM) functions such as pulse coded modulation (PCM). 
       FIG. 1C  illustrates another alternative embodiments of a data processing system capable of executing instructions to provide SIMD address conflict detection functionality. In accordance with one alternative embodiment, data processing system  160  may include a main processor  166 , a SIMD coprocessor  161 , a cache memory  167 , and an input/output system  168 . The input/output system  168  may optionally be coupled to a wireless interface  169 . SIMD coprocessor  161  is capable of performing operations including instructions in accordance with one embodiment. Processing core  170  may be suitable for manufacture in one or more process technologies and by being represented on a machine readable media in sufficient detail, may be suitable to facilitate the manufacture of all or part of data processing system  160  including processing core  170 . 
     For one embodiment, SIMD coprocessor  161  comprises an execution unit  162  and a set of register file(s)  164 . One embodiment of main processor  166  comprises a decoder  165  to recognize instructions of instruction set  163  including instructions in accordance with one embodiment for execution by execution unit  162 . For alternative embodiments, SIMD coprocessor  161  also comprises at least part of decoder  165 B to decode instructions of instruction set  163 . Processing core  170  also includes additional circuitry (not shown) which is not necessary to the understanding of embodiments of the present invention. 
     In operation, the main processor  166  executes a stream of data processing instructions that control data processing operations of a general type including interactions with the cache memory  167 , and the input/output system  168 . Embedded within the stream of data processing instructions are SIMD coprocessor instructions. The decoder  165  of main processor  166  recognizes these SIMD coprocessor instructions as being of a type that should be executed by an attached SIMD coprocessor  161 . Accordingly, the main processor  166  issues these SIMD coprocessor instructions (or control signals representing SIMD coprocessor instructions) on the coprocessor bus  171  where from they are received by any attached SIMD coprocessors. In this case, the SIMD coprocessor  161  will accept and execute any received SIMD coprocessor instructions intended for it. 
     Data may be received via wireless interface  169  for processing by the SIMD coprocessor instructions. For one example, voice communication may be received in the form of a digital signal, which may be processed by the SIMD coprocessor instructions to regenerate digital audio samples representative of the voice communications. For another example, compressed audio and/or video may be received in the form of a digital bit stream, which may be processed by the SIMD coprocessor instructions to regenerate digital audio samples and/or motion video frames. For one embodiment of processing core  170 , main processor  166 , and a SIMD coprocessor  161  are integrated into a single processing core  170  comprising an execution unit  162 , a set of register file(s)  164 , and a decoder  165  to recognize instructions of instruction set  163  including instructions in accordance with one embodiment. 
       FIG. 2  is a block diagram of the micro-architecture for a processor  200  that includes logic circuits to perform instructions in accordance with one embodiment of the present invention. In some embodiments, an instruction in accordance with one embodiment can be implemented to operate on data elements having sizes of byte, word, doubleword, quadword, etc., as well as datatypes, such as single and double precision integer and floating point datatypes. In one embodiment the in-order front end  201  is the part of the processor  200  that fetches instructions to be executed and prepares them to be used later in the processor pipeline. The front end  201  may include several units. In one embodiment, the instruction prefetcher  226  fetches instructions from memory and feeds them to an instruction decoder  228  which in turn decodes or interprets them. For example, in one embodiment, the decoder decodes a received instruction into one or more operations called “microinstructions” or “micro-operations” (also called micro op or uops) that the machine can execute. In other embodiments, the decoder parses the instruction into an opcode and corresponding data and control fields that are used by the micro-architecture to perform operations in accordance with one embodiment. In one embodiment, the trace cache  230  takes decoded uops and assembles them into program ordered sequences or traces in the uop queue  234  for execution. When the trace cache  230  encounters a complex instruction, the microcode ROM  232  provides the uops needed to complete the operation. 
     Some instructions are converted into a single micro-op, whereas others need several micro-ops to complete the full operation. In one embodiment, if more than four micro-ops are needed to complete a instruction, the decoder  228  accesses the microcode ROM  232  to do the instruction. For one embodiment, an instruction can be decoded into a small number of micro ops for processing at the instruction decoder  228 . In another embodiment, an instruction can be stored within the microcode ROM  232  should a number of micro-ops be needed to accomplish the operation. The trace cache  230  refers to a entry point programmable logic array (PLA) to determine a correct micro-instruction pointer for reading the micro-code sequences to complete one or more instructions in accordance with one embodiment from the micro-code ROM  232 . After the microcode ROM  232  finishes sequencing micro-ops for an instruction, the front end  201  of the machine resumes fetching micro-ops from the trace cache  230 . 
     The out-of-order execution engine  203  is where the instructions are prepared for execution. The out-of-order execution logic has a number of buffers to smooth out and reorder the flow of instructions to optimize performance as they go down the pipeline and get scheduled for execution. The allocator logic allocates the machine buffers and resources that each uop needs in order to execute. The register renaming logic renames logic registers onto entries in a register file. The allocator also allocates an entry for each uop in one of the two uop queues, one for memory operations and one for non-memory operations, in front of the instruction schedulers: memory scheduler, fast scheduler  202 , slow/general floating point scheduler  204 , and simple floating point scheduler  206 . The uop schedulers  202 ,  204 ,  206 , determine when a uop is ready to execute based on the readiness of their dependent input register operand sources and the availability of the execution resources the uops need to complete their operation. The fast scheduler  202  of one embodiment can schedule on each half of the main clock cycle while the other schedulers can only schedule once per main processor clock cycle. The schedulers arbitrate for the dispatch ports to schedule uops for execution. 
     Register files  208 ,  210 , sit between the schedulers  202 ,  204 ,  206 , and the execution units  212 ,  214 ,  216 ,  218 ,  220 ,  222 ,  224  in the execution block  211 . There is a separate register file  208 ,  210 , for integer and floating point operations, respectively. Each register file  208 ,  210 , of one embodiment also includes a bypass network that can bypass or forward just completed results that have not yet been written into the register file to new dependent uops. The integer register file  208  and the floating point register file  210  are also capable of communicating data with the other. For one embodiment, the integer register file  208  is split into two separate register files, one register file for the low order 32 bits of data and a second register file for the high order 32 bits of data. The floating point register file  210  of one embodiment has 128 bit wide entries because floating point instructions typically have operands from 64 to 128 bits in width. 
     The execution block  211  contains the execution units  212 ,  214 ,  216 ,  218 ,  220 ,  222 ,  224 , where the instructions are actually executed. This section includes the register files  208 ,  210 , that store the integer and floating point data operand values that the microinstructions need to execute. The processor  200  of one embodiment is comprised of a number of execution units: address generation unit (AGU)  212 , AGU  214 , fast ALU  216 , fast ALU  218 , slow ALU  220 , floating point ALU  222 , floating point move unit  224 . For one embodiment, the floating point execution blocks  222 ,  224 , execute floating point, MMX, SIMD, and SSE, or other operations. The floating point ALU  222  of one embodiment includes a 64 bit by 64 bit floating point divider to execute divide, square root, and remainder micro-ops. For embodiments of the present invention, instructions involving a floating point value may be handled with the floating point hardware. In one embodiment, the ALU operations go to the high-speed ALU execution units  216 ,  218 . The fast ALUs  216 ,  218 , of one embodiment can execute fast operations with an effective latency of half a clock cycle. For one embodiment, most complex integer operations go to the slow ALU  220  as the slow ALU  220  includes integer execution hardware for long latency type of operations, such as a multiplier, shifts, flag logic, and branch processing. Memory load/store operations are executed by the AGUs  212 ,  214 . For one embodiment, the integer ALUs  216 ,  218 ,  220 , are described in the context of performing integer operations on 64 bit data operands. In alternative embodiments, the ALUs  216 ,  218 ,  220 , can be implemented to support a variety of data bits including 16, 32, 128, 256, etc. Similarly, the floating point units  222 ,  224 , can be implemented to support a range of operands having bits of various widths. For one embodiment, the floating point units  222 ,  224 , can operate on 128 bits wide packed data operands in conjunction with SIMD and multimedia instructions. 
     In one embodiment, the uops schedulers  202 ,  204 ,  206 , dispatch dependent operations before the parent load has finished executing. As uops are speculatively scheduled and executed in processor  200 , the processor  200  also includes logic to handle memory misses. If a data load misses in the data cache, there can be dependent operations in flight in the pipeline that have left the scheduler with temporarily incorrect data. A replay mechanism tracks and re-executes instructions that use incorrect data. Only the dependent operations need to be replayed and the independent ones are allowed to complete. The schedulers and replay mechanism of one embodiment of a processor are also designed to catch instructions that provide SIMD address conflict detection functionality. 
     The term “registers” may refer to the on-board processor storage locations that are used as part of instructions to identify operands. In other words, registers may be those that are usable from the outside of the processor (from a programmer&#39;s perspective). However, the registers of an embodiment should not be limited in meaning to a particular type of circuit. Rather, a register of an embodiment is capable of storing and providing data, and performing the functions described herein. The registers described herein can be implemented by circuitry within a processor using any number of different techniques, such as dedicated physical registers, dynamically allocated physical registers using register renaming, combinations of dedicated and dynamically allocated physical registers, etc. In one embodiment, integer registers store thirty-two bit integer data. A register file of one embodiment also contains eight multimedia SIMD registers for packed data. For the discussions below, the registers are understood to be data registers designed to hold packed data, such as 64 bits wide MMX™ registers (also referred to as ‘mm’ registers in some instances) in microprocessors enabled with MMX technology from Intel Corporation of Santa Clara, Calif. These MMX registers, available in both integer and floating point forms, can operate with packed data elements that accompany SIMD and SSE instructions. Similarly, 128 bits wide XMM registers relating to SSE2, SSE3, SSE4, or beyond (referred to generically as “SSEx”) technology can also be used to hold such packed data operands. In one embodiment, in storing packed data and integer data, the registers do not need to differentiate between the two data types. In one embodiment, integer and floating point are either contained in the same register file or different register files. Furthermore, in one embodiment, floating point and integer data may be stored in different registers or the same registers. 
     In the examples of the following figures, a number of data operands are described.  FIG. 3A  illustrates various packed data type representations in multimedia registers according to one embodiment of the present invention.  FIG. 3A  illustrates data types for a packed byte  310 , a packed word  320 , and a packed doubleword (dword)  330  for 128 bits wide operands. The packed byte format  310  of this example is 128 bits long and contains sixteen packed byte data elements. A byte is defined here as 8 bits of data. Information for each byte data element is stored in bit  7  through bit  0  for byte  0 , bit  15  through bit  8  for byte  1 , bit  23  through bit  16  for byte  2 , and finally bit  120  through bit  127  for byte  15 . Thus, all available bits are used in the register. This storage arrangement increases the storage efficiency of the processor. As well, with sixteen data elements accessed, one operation can now be performed on sixteen data elements in parallel. 
     Generally, a data element is an individual piece of data that is stored in a single register or memory location with other data elements of the same length. In packed data sequences relating to SSEx technology, the number of data elements stored in a XMM register is 128 bits divided by the length in bits of an individual data element. Similarly, in packed data sequences relating to MMX and SSE technology, the number of data elements stored in an MMX register is 64 bits divided by the length in bits of an individual data element. Although the data types illustrated in  FIG. 3A  are 128 bit long, embodiments of the present invention can also operate with 64 bit wide, 256 bit wide, 512 bit wide, or other sized operands. The packed word format  320  of this example is 128 bits long and contains eight packed word data elements. Each packed word contains sixteen bits of information. The packed doubleword format  330  of  FIG. 3A  is 128 bits long and contains four packed doubleword data elements. Each packed doubleword data element contains thirty two bits of information. A packed quadword is 128 bits long and contains two packed quad-word data elements. 
       FIG. 3B  illustrates alternative in-register data storage formats. Each packed data can include more than one independent data element. Three packed data formats are illustrated; packed half  341 , packed single  342 , and packed double  343 . One embodiment of packed half  341 , packed single  342 , and packed double  343  contain fixed-point data elements. For an alternative embodiment one or more of packed half  341 , packed single  342 , and packed double  343  may contain floating-point data elements. One alternative embodiment of packed half  341  is one hundred twenty-eight bits long containing eight 16-bit data elements. One embodiment of packed single  342  is one hundred twenty-eight bits long and contains four 32-bit data elements. One embodiment of packed double  343  is one hundred twenty-eight bits long and contains two 64-bit data elements. It will be appreciated that such packed data formats may be further extended to other register lengths, for example, to 96-bits, 160-bits, 192-bits, 224-bits, 256-bits, 512-bits or more. 
       FIG. 3C  illustrates various signed and unsigned packed data type representations in multimedia registers according to one embodiment of the present invention. Unsigned packed byte representation  344  illustrates the storage of an unsigned packed byte in a SIMD register. Information for each byte data element is stored in bit seven through bit zero for byte zero, bit fifteen through bit eight for byte one, bit twenty-three through bit sixteen for byte two, etc., and finally bit one hundred twenty through bit one hundred twenty-seven for byte fifteen. Thus, all available bits are used in the register. This storage arrangement can increase the storage efficiency of the processor. As well, with sixteen data elements accessed, one operation can now be performed on sixteen data elements in a parallel fashion. Signed packed byte representation  345  illustrates the storage of a signed packed byte. Note that the eighth bit of every byte data element is the sign indicator. Unsigned packed word representation  346  illustrates how word seven through word zero are stored in a SIMD register. Signed packed word representation  347  is similar to the unsigned packed word in-register representation  346 . Note that the sixteenth bit of each word data element is the sign indicator. Unsigned packed doubleword representation  348  shows how doubleword data elements are stored. Signed packed doubleword representation  349  is similar to unsigned packed doubleword in-register representation  348 . Note that the necessary sign bit is the thirty-second bit of each doubleword data element. 
       FIG. 3D  is a depiction of one embodiment of an operation encoding (opcode) format  360 , having thirty-two or more bits, and register/memory operand addressing modes corresponding with a type of opcode format described in the “Intel® 64 and IA-32 Intel Architecture Software Developer&#39;s Manual Combined Volumes 2A and 2B: Instruction Set Reference A-Z,” which is which is available from Intel Corporation, Santa Clara, Calif. on the world-wide-web (www) at intel.com/products/processor/manuals/. In one embodiment, and instruction may be encoded by one or more of fields  361  and  362 . Up to two operand locations per instruction may be identified, including up to two source operand identifiers  364  and  365 . For one embodiment, destination operand identifier  366  is the same as source operand identifier  364 , whereas in other embodiments they are different. For an alternative embodiment, destination operand identifier  366  is the same as source operand identifier  365 , whereas in other embodiments they are different. In one embodiment, one of the source operands identified by source operand identifiers  364  and  365  is overwritten by the results of the instruction, whereas in other embodiments identifier  364  corresponds to a source register element and identifier  365  corresponds to a destination register element. For one embodiment, operand identifiers  364  and  365  may be used to identify 32-bit or 64-bit source and destination operands. 
       FIG. 3E  is a depiction of another alternative operation encoding (opcode) format  370 , having forty or more bits. Opcode format  370  corresponds with opcode format  360  and comprises an optional prefix byte  378 . An instruction according to one embodiment may be encoded by one or more of fields  378 ,  371 , and  372 . Up to two operand locations per instruction may be identified by source operand identifiers  374  and  375  and by prefix byte  378 . For one embodiment, prefix byte  378  may be used to identify 32-bit or 64-bit source and destination operands. For one embodiment, destination operand identifier  376  is the same as source operand identifier  374 , whereas in other embodiments they are different. For an alternative embodiment, destination operand identifier  376  is the same as source operand identifier  375 , whereas in other embodiments they are different. In one embodiment, an instruction operates on one or more of the operands identified by operand identifiers  374  and  375  and one or more operands identified by the operand identifiers  374  and  375  is overwritten by the results of the instruction, whereas in other embodiments, operands identified by identifiers  374  and  375  are written to another data element in another register. Opcode formats  360  and  370  allow register to register, memory to register, register by memory, register by register, register by immediate, register to memory addressing specified in part by MOD fields  363  and  373  and by optional scale-index-base and displacement bytes. 
     Turning next to  FIG. 3F , in some alternative embodiments, 64-bit (or 128-bit, or 256-bit, or 512-bit or more) single instruction multiple data (SIMD) arithmetic operations may be performed through a coprocessor data processing (CDP) instruction. Operation encoding (opcode) format  380  depicts one such CDP instruction having CDP opcode fields  382  and  389 . The type of CDP instruction, for alternative embodiments, operations may be encoded by one or more of fields  383 ,  384 ,  387 , and  388 . Up to three operand locations per instruction may be identified, including up to two source operand identifiers  385  and  390  and one destination operand identifier  386 . One embodiment of the coprocessor can operate on 8, 16, 32, and 64 bit values. For one embodiment, an instruction is performed on integer data elements. In some embodiments, an instruction may be executed conditionally, using condition field  381 . For some embodiments, source data sizes may be encoded by field  383 . In some embodiments, Zero (Z), negative (N), carry (C), and overflow (V) detection can be done on SIMD fields. For some instructions, the type of saturation may be encoded by field  384 . 
     Turning next to  FIG. 3G  is a depiction of another alternative operation encoding (opcode) format  397 , to provide SIMD address conflict detection functionality according to another embodiment, corresponding with a type of opcode format described in the “Intel® Advanced Vector Extensions Programming Reference,” which is available from Intel Corp., Santa Clara, Calif. on the world-wide-web (www) at intel.com/products/processor/manuals/. 
     The original x86 instruction set provided for a 1-byte opcode with various formats of address syllable and immediate operand contained in additional bytes whose presence was known from the first “opcode” byte. Additionally, there were certain byte values that were reserved as modifiers to the opcode (called prefixes, as they had to be placed before the instruction). When the original palette of 256 opcode bytes (including these special prefix values) was exhausted, a single byte was dedicated as an escape to a new set of 256 opcodes. As vector instructions (e.g., SIMD) were added, a need for more opcodes was generated, and the “two byte” opcode map also was insufficient, even when expanded through the use of prefixes. To this end, new instructions were added in additional maps which use 2 bytes plus an optional prefix as an identifier. 
     Additionally, in order to facilitate additional registers in 64-bit mode, an additional prefix may be used (called “REX”) in between the prefixes and the opcode (and any escape bytes necessary to determine the opcode). In one embodiment, the REX may have 4 “payload” bits to indicate use of additional registers in 64-bit mode. In other embodiments it may have fewer or more than 4 bits. The general format of at least one instruction set (which corresponds generally with format  360  and/or format  370 ) is illustrated generically by the following:
         [prefixes] [rex] escape [escape2] opcode modrm (etc.)       

     Opcode format  397  corresponds with opcode format  370  and comprises optional VEX prefix bytes  391  (beginning with C4 hex in one embodiment) to replace most other commonly used legacy instruction prefix bytes and escape codes. For example, the following illustrates an embodiment using two fields to encode an instruction, which may be used when a second escape code is present in the original instruction, or when extra bits (e.g, the XB and W fields) in the REX field need to be used. In the embodiment illustrated below, legacy escape is represented by a new escape value, legacy prefixes are fully compressed as part of the “payload” bytes, legacy prefixes are reclaimed and available for future expansion, the second escape code is compressed in a “map” field, with future map or feature space available, and new features are added (e.g., increased vector length and an additional source register specifier). 
     
       
         
         
             
             
         
       
     
     An instruction according to one embodiment may be encoded by one or more of fields  391  and  392 . Up to four operand locations per instruction may be identified by field  391  in combination with source operand identifiers  374  and  375  and in combination with an optional scale-index-base (SIB) identifier  393 , an optional displacement identifier  394 , and an optional immediate byte  395 . For one embodiment, VEX prefix bytes  391  may be used to identify 32-bit or 64-bit source and destination operands and/or 128-bit or 256-bit SIMD register or memory operands. For one embodiment, the functionality provided by opcode format  397  may be redundant with opcode format  370 , whereas in other embodiments they are different. Opcode formats  370  and  397  allow register to register, memory to register, register by memory, register by register, register by immediate, register to memory addressing specified in part by MOD field  373  and by optional (SIB) identifier  393 , an optional displacement identifier  394 , and an optional immediate byte  395 . 
     Turning next to  FIG. 3H  is a depiction of another alternative operation encoding (opcode) format  398 , to provide SIMD address conflict detection functionality according to another embodiment. Opcode format  398  corresponds with opcode formats  370  and  397  and comprises optional EVEX prefix bytes  396  (beginning with 62 hex in one embodiment) to replace most other commonly used legacy instruction prefix bytes and escape codes and provide additional functionality. An instruction according to one embodiment may be encoded by one or more of fields  396  and  392 . Up to four operand locations per instruction and a mask may be identified by field  396  in combination with source operand identifiers  374  and  375  and in combination with an optional scale-index-base (SIB) identifier  393 , an optional displacement identifier  394 , and an optional immediate byte  395 . For one embodiment, EVEX prefix bytes  396  may be used to identify 32-bit or 64-bit source and destination operands and/or 128-bit, 256-bit or 512-bit SIMD register or memory operands. For one embodiment, the functionality provided by opcode format  398  may be redundant with opcode formats  370  or  397 , whereas in other embodiments they are different. Opcode format  398  allows register to register, memory to register, register by memory, register by register, register by immediate, register to memory addressing, with masks, specified in part by MOD field  373  and by optional (SIB) identifier  393 , an optional displacement identifier  394 , and an optional immediate byte  395 . The general format of at least one instruction set (which corresponds generally with format  360  and/or format  370 ) is illustrated generically by the following:
         evex1 RXBmmmmm WvvvLpp evex4 opcode modrm [sib] [disp] [imm]       

     For one embodiment an instruction encoded according to the EVEX format  398  may have additional “payload” bits that may be used to provide SIMD address conflict detection functionality with additional new features such as, for example, a user configurable mask register, or an additional operand, or selections from among 128-bit, 256-bit or 512-bit vector registers, or more registers from which to select, etc. 
     For example, where VEX format  397  may be used to provide SIMD address conflict detection functionality without a mask, the EVEX format  398  may be used to provide SIMD address conflict detection functionality with an explicit user configurable mask. Additionally, where VEX format  397  may be used to provide SIMD address conflict detection functionality on 128-bit or 256-bit vector registers, EVEX format  398  may be used to provide SIMD address conflict detection functionality on 128-bit, 256-bit, 512-bit or larger (or smaller) vector registers. 
     Example instructions to provide SIMD vector leading zero count functionality, SIMD vector address conflict detection functionality, and SIMD vector population count functionality for efficient vector address conflict resolution are illustrated by the following examples: 
     
       
         
           
               
               
               
               
               
             
               
                   
               
               
                   
                 desti- 
                   
                   
                   
               
               
                 Instruction 
                 nation 
                 source1 
                 source2 
                 description 
               
               
                   
               
             
            
               
                 VPLZCNTD 
                 Vmm1 
                 Vmm2/ 
                 Mask1 
                 For each 32-bit element in 
               
               
                   
                   
                 Mem1 
                   
                 the register Vmm2 or in a 
               
               
                   
                   
                   
                   
                 vector at memory location, 
               
               
                   
                   
                   
                   
                 Mem1, count the number 
               
               
                   
                   
                   
                   
                 of most significant 
               
               
                   
                   
                   
                   
                 contiguous bits set to zero  
               
               
                   
                   
                   
                   
                 and store the counts as 
               
               
                   
                   
                   
                   
                 corresponding elements 
               
               
                   
                   
                   
                   
                 in the register Vmm1. 
               
               
                 VPLZCNTQ 
                 Vmm1 
                 Vmm2/ 
                 Mask1 
                 For each 64-bit element in  
               
               
                   
                   
                 Mem1 
                   
                 the register Vmm2 or in a  
               
               
                   
                   
                   
                   
                 vector at memory location,  
               
               
                   
                   
                   
                   
                 Mem1, count the number 
               
               
                   
                   
                   
                   
                 of most significant 
               
               
                   
                   
                   
                   
                 contiguous bits set to zero  
               
               
                   
                   
                   
                   
                 and store the counts as  
               
               
                   
                   
                   
                   
                 corresponding elements 
               
               
                   
                   
                   
                   
                 in the register Vmm1. 
               
               
                 VPCONFLICTD 
                 Vmm1 
                 Vmm2/ 
                 Mask1 
                 For each 32-bit element in  
               
               
                   
                   
                 Mem1 
                   
                 the register Vmm2 or  
               
               
                   
                   
                   
                   
                 in a vector at memory 
               
               
                   
                   
                   
                   
                 location, Mem1,  
               
               
                   
                   
                   
                   
                 compare it with every 
               
               
                   
                   
                   
                   
                 less significant element  
               
               
                   
                   
                   
                   
                 to determine if they hold 
               
               
                   
                   
                   
                   
                 matching offsets, and in 
               
               
                   
                   
                   
                   
                 a corresponding element in 
               
               
                   
                   
                   
                   
                 the destination register,  
               
               
                   
                   
                   
                   
                 Vmm1, set any mask bits  
               
               
                   
                   
                   
                   
                 corresponding to a less  
               
               
                   
                   
                   
                   
                 significant data field 
               
               
                   
                   
                   
                   
                 holding a matching offset  
               
               
                   
                   
                   
                   
                 to one. Set all other bits in  
               
               
                   
                   
                   
                   
                 Vmm1 to zero. 
               
               
                 VPCONFLICTQ 
                 Vmm1 
                 Vmm2/ 
                 Mask1 
                 For each 64-bit element in  
               
               
                   
                   
                 Mem1 
                   
                 the register Vmm2 or in a  
               
               
                   
                   
                   
                   
                 vector at memory location,  
               
               
                   
                   
                   
                   
                 Mem1, compare it with 
               
               
                   
                   
                   
                   
                 every less significant 
               
               
                   
                   
                   
                   
                 element to determine 
               
               
                   
                   
                   
                   
                 if they hold matching 
               
               
                   
                   
                   
                   
                 offsets, and in a 
               
               
                   
                   
                   
                   
                 corresponding element  
               
               
                   
                   
                   
                   
                 in the destination register,  
               
               
                   
                   
                   
                   
                 Vmm1, set any mask bits 
               
               
                   
                   
                   
                   
                 corresponding to a less  
               
               
                   
                   
                   
                   
                 significant data field  
               
               
                   
                   
                   
                   
                 holding a matching offset  
               
               
                   
                   
                   
                   
                 to one. Set all other 
               
               
                   
                   
                   
                   
                 bits in Vmm1 to zero. 
               
               
                 VPOPCNTD 
                 Vmm1 
                 Vmm2/ 
                 Mask1 
                 For each 32-bit element in  
               
               
                   
                   
                 Mem1 
                   
                 the register Vmm2 or in a  
               
               
                   
                   
                   
                   
                 vector at memory location, 
               
               
                   
                   
                   
                   
                 Mem1, count the number 
               
               
                   
                   
                   
                   
                 of bits set to one and 
               
               
                   
                   
                   
                   
                 store the counts as 
               
               
                   
                   
                   
                   
                 corresponding elements 
               
               
                   
                   
                   
                   
                 in the register Vmm1. 
               
               
                 VPOPCNTQ 
                 Vmm1 
                 Vmm2/ 
                 Mask1 
                 For each 64-bit element in  
               
               
                   
                   
                 Mem1 
                   
                 the register Vmm2 or in a  
               
               
                   
                   
                   
                   
                 vector at memory location,  
               
               
                   
                   
                   
                   
                 Mem1, count the number  
               
               
                   
                   
                   
                   
                 of bits set to one and  
               
               
                   
                   
                   
                   
                 store the counts as 
               
               
                   
                   
                   
                   
                 corresponding elements 
               
               
                   
                   
                   
                   
                 in the register Vmm1. 
               
               
                   
               
            
           
         
       
     
     It will be appreciated that SIMD vector conflict instructions, as in the examples above, may be used for variable sized elements and memory offsets to provide SIMD vector address conflict detection functionality and to generate conflict masks for efficient SIMD address conflict resolution. It will also be appreciated that SIMD vector leading zero count instructions, as in the examples above, may be used with variable sized elements and conflict masks to provide SIMD permute controls, which will be described in greater detail below, thereby permitting more efficient SIMD address conflict resolution in registers without performing dependent computations through memory. It will further be appreciated that SIMD vector population count instructions, as in the examples above, may be used with variable sized elements and conflict masks to efficiently compute iteration counts and to provide SIMD completion masks for each iteration of a SIMD address conflict resolution, which will be described in greater detail below. Thus the instructions disclosed herein provide for more efficient SIMD address conflict resolution especially in gather-modify-scatter applications. 
       FIG. 4A  is a block diagram illustrating an in-order pipeline and a register renaming stage, out-of-order issue/execution pipeline according to at least one embodiment of the invention.  FIG. 4B  is a block diagram illustrating an in-order architecture core and a register renaming logic, out-of-order issue/execution logic to be included in a processor according to at least one embodiment of the invention. The solid lined boxes in  FIG. 4A  illustrate the in-order pipeline, while the dashed lined boxes illustrates the register renaming, out-of-order issue/execution pipeline. Similarly, the solid lined boxes in  FIG. 4B  illustrate the in-order architecture logic, while the dashed lined boxes illustrates the register renaming logic and out-of-order issue/execution logic. 
     In  FIG. 4A , a processor pipeline  400  includes a fetch stage  402 , a length decode stage  404 , a decode stage  406 , an allocation stage  408 , a renaming stage  410 , a scheduling (also known as a dispatch or issue) stage  412 , a register read/memory read stage  414 , an execute stage  416 , a write back/memory write stage  418 , an exception handling stage  422 , and a commit stage  424 . 
     In  FIG. 4B , arrows denote a coupling between two or more units and the direction of the arrow indicates a direction of data flow between those units.  FIG. 4B  shows processor core  490  including a front end unit  430  coupled to an execution engine unit  450 , and both are coupled to a memory unit  470 . 
     The core  490  may be a reduced instruction set computing (RISC) core, a complex instruction set computing (CISC) core, a very long instruction word (VLIW) core, or a hybrid or alternative core type. As yet another option, the core  490  may be a special-purpose core, such as, for example, a network or communication core, compression engine, graphics core, or the like. 
     The front end unit  430  includes a branch prediction unit  432  coupled to an instruction cache unit  434 , which is coupled to an instruction translation lookaside buffer (TLB)  436 , which is coupled to an instruction fetch unit  438 , which is coupled to a decode unit  440 . The decode unit or decoder may decode instructions, and generate as an output one or more micro-operations, micro-code entry points, microinstructions, other instructions, or other control signals, which are decoded from, or which otherwise reflect, or are derived from, the original instructions. The decoder may be implemented using various different mechanisms. Examples of suitable mechanisms include, but are not limited to, look-up tables, hardware implementations, programmable logic arrays (PLAs), microcode read only memories (ROMs), etc. The instruction cache unit  434  is further coupled to a level 2 (L2) cache unit  476  in the memory unit  470 . The decode unit  440  is coupled to a rename/allocator unit  452  in the execution engine unit  450 . 
     The execution engine unit  450  includes the rename/allocator unit  452  coupled to a retirement unit  454  and a set of one or more scheduler unit(s)  456 . The scheduler unit(s)  456  represents any number of different schedulers, including reservations stations, central instruction window, etc. The scheduler unit(s)  456  is coupled to the physical register file(s) unit(s)  458 . Each of the physical register file(s) units  458  represents one or more physical register files, different ones of which store one or more different data types, such as scalar integer, scalar floating point, packed integer, packed floating point, vector integer, vector floating point, etc., status (e.g., an instruction pointer that is the address of the next instruction to be executed), etc. The physical register file(s) unit(s)  458  is overlapped by the retirement unit  454  to illustrate various ways in which register renaming and out-of-order execution may be implemented (e.g., using a reorder buffer(s) and a retirement register file(s), using a future file(s), a history buffer(s), and a retirement register file(s); using a register maps and a pool of registers; etc.). Generally, the architectural registers are visible from the outside of the processor or from a programmer&#39;s perspective. The registers are not limited to any known particular type of circuit. Various different types of registers are suitable as long as they are capable of storing and providing data as described herein. Examples of suitable registers include, but are not limited to, dedicated physical registers, dynamically allocated physical registers using register renaming, combinations of dedicated and dynamically allocated physical registers, etc. The retirement unit  454  and the physical register file(s) unit(s)  458  are coupled to the execution cluster(s)  460 . The execution cluster(s)  460  includes a set of one or more execution units  462  and a set of one or more memory access units  464 . The execution units  462  may perform various operations (e.g., shifts, addition, subtraction, multiplication) and on various types of data (e.g., scalar floating point, packed integer, packed floating point, vector integer, vector floating point). While some embodiments may include a number of execution units dedicated to specific functions or sets of functions, other embodiments may include only one execution unit or multiple execution units that all perform all functions. The scheduler unit(s)  456 , physical register file(s) unit(s)  458 , and execution cluster(s)  460  are shown as being possibly plural because certain embodiments create separate pipelines for certain types of data/operations (e.g., a scalar integer pipeline, a scalar floating point/packed integer/packed floating point/vector integer/vector floating point pipeline, and/or a memory access pipeline that each have their own scheduler unit, physical register file(s) unit, and/or execution cluster, and in the case of a separate memory access pipeline, certain embodiments are implemented in which only the execution cluster of this pipeline has the memory access unit(s)  464 ). It should also be understood that where separate pipelines are used, one or more of these pipelines may be out-of-order issue/execution and the rest in-order. 
     The set of memory access units  464  is coupled to the memory unit  470 , which includes a data TLB unit  472  coupled to a data cache unit  474  coupled to a level 2 (L2) cache unit  476 . In one exemplary embodiment, the memory access units  464  may include a load unit, a store address unit, and a store data unit, each of which is coupled to the data TLB unit  472  in the memory unit  470 . The L2 cache unit  476  is coupled to one or more other levels of cache and eventually to a main memory. 
     By way of example, the exemplary register renaming, out-of-order issue/execution core architecture may implement the pipeline  400  as follows: 1) the instruction fetch  438  performs the fetch and length decoding stages  402  and  404 ; 2) the decode unit  440  performs the decode stage  406 ; 3) the rename/allocator unit  452  performs the allocation stage  408  and renaming stage  410 ; 4) the scheduler unit(s)  456  performs the schedule stage  412 ; 5) the physical register file(s) unit(s)  458  and the memory unit  470  perform the register read/memory read stage  414 ; the execution cluster  460  perform the execute stage  416 ; 6) the memory unit  470  and the physical register file(s) unit(s)  458  perform the write back/memory write stage  418 ; 7) various units may be involved in the exception handling stage  422 ; and 8) the retirement unit  454  and the physical register file(s) unit(s)  458  perform the commit stage  424 . 
     The core  490  may support one or more instructions sets (e.g., the x86 instruction set (with some extensions that have been added with newer versions); the MIPS instruction set of MIPS Technologies of Sunnyvale, Calif.; the ARM instruction set (with optional additional extensions such as NEON) of ARM Holdings of Sunnyvale, Calif.). 
     It should be understood that the core may support multithreading (executing two or more parallel sets of operations or threads), and may do so in a variety of ways including time sliced multithreading, simultaneous multithreading (where a single physical core provides a logical core for each of the threads that physical core is simultaneously multithreading), or a combination thereof (e.g., time sliced fetching and decoding and simultaneous multithreading thereafter such as in the Intel® Hyperthreading technology). 
     While register renaming is described in the context of out-of-order execution, it should be understood that register renaming may be used in an in-order architecture. While the illustrated embodiment of the processor also includes a separate instruction and data cache units  434 / 474  and a shared L2 cache unit  476 , alternative embodiments may have a single internal cache for both instructions and data, such as, for example, a Level 1 (L1) internal cache, or multiple levels of internal cache. In some embodiments, the system may include a combination of an internal cache and an external cache that is external to the core and/or the processor. Alternatively, all of the cache may be external to the core and/or the processor. 
       FIG. 5  is a block diagram of a single core processor and a multicore processor  500  with integrated memory controller and graphics according to embodiments of the invention. The solid lined boxes in  FIG. 5  illustrate a processor  500  with a single core  502 A, a system agent  510 , a set of one or more bus controller units  516 , while the optional addition of the dashed lined boxes illustrates an alternative processor  500  with multiple cores  502 A-N, a set of one or more integrated memory controller unit(s)  514  in the system agent unit  510 , and an integrated graphics logic  508 . 
     The memory hierarchy includes one or more levels of cache within the cores, a set or one or more shared cache units  506 , and external memory (not shown) coupled to the set of integrated memory controller units  514 . The set of shared cache units  506  may include one or more mid-level caches, such as level 2 (L2), level 3 (L3), level 4 (L4), or other levels of cache, a last level cache (LLC), and/or combinations thereof. While in one embodiment a ring based interconnect unit  512  interconnects the integrated graphics logic  508 , the set of shared cache units  506 , and the system agent unit  510 , alternative embodiments may use any number of well-known techniques for interconnecting such units. 
     In some embodiments, one or more of the cores  502 A-N are capable of multithreading. The system agent  510  includes those components coordinating and operating cores  502 A-N. The system agent unit  510  may include for example a power control unit (PCU) and a display unit. The PCU may be or include logic and components needed for regulating the power state of the cores  502 A-N and the integrated graphics logic  508 . The display unit is for driving one or more externally connected displays. 
     The cores  502 A-N may be homogenous or heterogeneous in terms of architecture and/or instruction set. For example, some of the cores  502 A-N may be in order while others are out-of-order. As another example, two or more of the cores  502 A-N may be capable of execution the same instruction set, while others may be capable of executing only a subset of that instruction set or a different instruction set. 
     The processor may be a general-purpose processor, such as a Core™ i3, i5, i7, 2 Duo and Quad, Xeon™, Itanium™, XScale™ or StrongARM™ processor, which are available from Intel Corporation, of Santa Clara, Calif. Alternatively, the processor may be from another company, such as ARM Holdings, Ltd, MIPS, etc. The processor may be a special-purpose processor, such as, for example, a network or communication processor, compression engine, graphics processor, co-processor, embedded processor, or the like. The processor may be implemented on one or more chips. The processor  500  may be a part of and/or may be implemented on one or more substrates using any of a number of process technologies, such as, for example, BiCMOS, CMOS, or NMOS. 
       FIGS. 6-8  are exemplary systems suitable for including the processor  500 , while  FIG. 9  is an exemplary system on a chip (SoC) that may include one or more of the cores  502 . Other system designs and configurations known in the arts for laptops, desktops, handheld PCs, personal digital assistants, engineering workstations, servers, network devices, network hubs, switches, embedded processors, digital signal processors (DSPs), graphics devices, video game devices, set-top boxes, micro controllers, cell phones, portable media players, hand held devices, and various other electronic devices, are also suitable. In general, a huge variety of systems or electronic devices capable of incorporating a processor and/or other execution logic as disclosed herein are generally suitable. 
     Referring now to  FIG. 6 , shown is a block diagram of a system  600  in accordance with one embodiment of the present invention. The system  600  may include one or more processors  610 ,  615 , which are coupled to graphics memory controller hub (GMCH)  620 . The optional nature of additional processors  615  is denoted in  FIG. 6  with broken lines. 
     Each processor  610 , 615  may be some version of the processor  500 . However, it should be noted that it is unlikely that integrated graphics logic and integrated memory control units would exist in the processors  610 , 615 .  FIG. 6  illustrates that the GMCH  620  may be coupled to a memory  640  that may be, for example, a dynamic random access memory (DRAM). The DRAM may, for at least one embodiment, be associated with a non-volatile cache. 
     The GMCH  620  may be a chipset, or a portion of a chipset. The GMCH  620  may communicate with the processor(s)  610 ,  615  and control interaction between the processor(s)  610 ,  615  and memory  640 . The GMCH  620  may also act as an accelerated bus interface between the processor(s)  610 ,  615  and other elements of the system  600 . For at least one embodiment, the GMCH  620  communicates with the processor(s)  610 ,  615  via a multi-drop bus, such as a frontside bus (FSB)  695 . 
     Furthermore, GMCH  620  is coupled to a display  645  (such as a flat panel display). GMCH  620  may include an integrated graphics accelerator. GMCH  620  is further coupled to an input/output (I/O) controller hub (ICH)  650 , which may be used to couple various peripheral devices to system  600 . Shown for example in the embodiment of  FIG. 6  is an external graphics device  660 , which may be a discrete graphics device coupled to ICH  650 , along with another peripheral device  670 . 
     Alternatively, additional or different processors may also be present in the system  600 . For example, additional processor(s)  615  may include additional processors(s) that are the same as processor  610 , additional processor(s) that are heterogeneous or asymmetric to processor  610 , accelerators (such as, e.g., graphics accelerators or digital signal processing (DSP) units), field programmable gate arrays, or any other processor. There can be a variety of differences between the physical resources  610 ,  615  in terms of a spectrum of metrics of merit including architectural, micro-architectural, thermal, power consumption characteristics, and the like. These differences may effectively manifest themselves as asymmetry and heterogeneity amongst the processors  610 ,  615 . For at least one embodiment, the various processors  610 ,  615  may reside in the same die package. 
     Referring now to  FIG. 7 , shown is a block diagram of a second system  700  in accordance with an embodiment of the present invention. As shown in  FIG. 7 , multiprocessor system  700  is a point-to-point interconnect system, and includes a first processor  770  and a second processor  780  coupled via a point-to-point interconnect  750 . Each of processors  770  and  780  may be some version of the processor  500  as one or more of the processors  610 , 615 . 
     While shown with only two processors  770 ,  780 , it is to be understood that the scope of the present invention is not so limited. In other embodiments, one or more additional processors may be present in a given processor. 
     Processors  770  and  780  are shown including integrated memory controller units  772  and  782 , respectively. Processor  770  also includes as part of its bus controller units point-to-point (P-P) interfaces  776  and  778 ; similarly, second processor  780  includes P-P interfaces  786  and  788 . Processors  770 ,  780  may exchange information via a point-to-point (P-P) interface  750  using P-P interface circuits  778 ,  788 . As shown in  FIG. 7 , IMCs  772  and  782  couple the processors to respective memories, namely a memory  732  and a memory  734 , which may be portions of main memory locally attached to the respective processors. 
     Processors  770 ,  780  may each exchange information with a chipset  790  via individual P-P interfaces  752 ,  754  using point to point interface circuits  776 ,  794 ,  786 ,  798 . Chipset  790  may also exchange information with a high-performance graphics circuit  738  via a high-performance graphics interface  739 . 
     A shared cache (not shown) may be included in either processor or outside of both processors, yet connected with the processors via P-P interconnect, such that either or both processors&#39; local cache information may be stored in the shared cache if a processor is placed into a low power mode. 
     Chipset  790  may be coupled to a first bus  716  via an interface  796 . In one embodiment, first bus  716  may be a Peripheral Component Interconnect (PCI) bus, or a bus such as a PCI Express bus or another third generation I/O interconnect bus, although the scope of the present invention is not so limited. 
     As shown in  FIG. 7 , various I/O devices  714  may be coupled to first bus  716 , along with a bus bridge  718  which couples first bus  716  to a second bus  720 . In one embodiment, second bus  720  may be a low pin count (LPC) bus. Various devices may be coupled to second bus  720  including, for example, a keyboard and/or mouse  722 , communication devices  727  and a storage unit  728  such as a disk drive or other mass storage device which may include instructions/code and data  730 , in one embodiment. Further, an audio I/O  724  may be coupled to second bus  720 . Note that other architectures are possible. For example, instead of the point-to-point architecture of  FIG. 7 , a system may implement a multi-drop bus or other such architecture. 
     Referring now to  FIG. 8 , shown is a block diagram of a third system  800  in accordance with an embodiment of the present invention Like elements in  FIG. 7  and  FIG. 8  bear like reference numerals, and certain aspects of  FIG. 7  have been omitted from  FIG. 8  in order to avoid obscuring other aspects of  FIG. 8 . 
       FIG. 8  illustrates that the processors  870 ,  880  may include integrated memory and I/O control logic (“CL”)  872  and  882 , respectively. For at least one embodiment, the CL  872 ,  882  may include integrated memory controller units such as that described above in connection with  FIGS. 5 and 7 . In addition. CL  872 ,  882  may also include I/O control logic.  FIG. 8  illustrates that not only are the memories  832 ,  834  coupled to the CL  872 ,  882 , but also that I/O devices  814  are also coupled to the control logic  872 ,  882 . Legacy I/O devices  815  are coupled to the chipset  890 . 
     Referring now to  FIG. 9 , shown is a block diagram of a SoC  900  in accordance with an embodiment of the present invention. Similar elements in  FIG. 5  bear like reference numerals. Also, dashed lined boxes are optional features on more advanced SoCs. In  FIG. 9 , an interconnect unit(s)  902  is coupled to: an application processor  910  which includes a set of one or more cores  502 A-N and shared cache unit(s)  506 ; a system agent unit  510 ; a bus controller unit(s)  516 ; an integrated memory controller unit(s)  514 ; a set of one or more media processors  920  which may include integrated graphics logic  508 , an image processor  924  for providing still and/or video camera functionality, an audio processor  926  for providing hardware audio acceleration, and a video processor  928  for providing video encode/decode acceleration; an static random access memory (SRAM) unit  930 ; a direct memory access (DMA) unit  932 ; and a display unit  940  for coupling to one or more external displays. 
       FIG. 10  illustrates a processor containing a central processing unit (CPU) and a graphics processing unit (GPU), which may perform at least one instruction according to one embodiment. In one embodiment, an instruction to perform operations according to at least one embodiment could be performed by the CPU. In another embodiment, the instruction could be performed by the GPU. In still another embodiment, the instruction may be performed through a combination of operations performed by the GPU and the CPU. For example, in one embodiment, an instruction in accordance with one embodiment may be received and decoded for execution on the GPU. However, one or more operations within the decoded instruction may be performed by a CPU and the result returned to the GPU for final retirement of the instruction. Conversely, in some embodiments, the CPU may act as the primary processor and the GPU as the co-processor. 
     In some embodiments, instructions that benefit from highly parallel, throughput processors may be performed by the GPU, while instructions that benefit from the performance of processors that benefit from deeply pipelined architectures may be performed by the CPU. For example, graphics, scientific applications, financial applications and other parallel workloads may benefit from the performance of the GPU and be executed accordingly, whereas more sequential applications, such as operating system kernel or application code may be better suited for the CPU. 
     In  FIG. 10 , processor  1000  includes a CPU  1005 , GPU  1010 , image processor  1015 , video processor  1020 , USB controller  1025 , UART controller  1030 , SPI/SDIO controller  1035 , display device  1040 , High-Definition Multimedia Interface (HDMI) controller  1045 , MIPI controller  1050 , flash memory controller  1055 , dual data rate (DDR) controller  1060 , security engine  1065 , and I 2 S/I 2 C (Integrated Interchip Sound/Inter-Integrated Circuit) interface  1070 . Other logic and circuits may be included in the processor of  FIG. 10 , including more CPUs or GPUs and other peripheral interface controllers. 
     One or more aspects of at least one embodiment may be implemented by representative data stored on a machine-readable medium which represents various logic within the processor, which when read by a machine causes the machine to fabricate logic to perform the techniques described herein. Such representations, known as “IP cores” may be stored on a tangible, machine readable medium (“tape”) and supplied to various customers or manufacturing facilities to load into the fabrication machines that actually make the logic or processor. For example, IP cores, such as the Cortex™ family of processors developed by ARM Holdings, Ltd. and Loongson IP cores developed the Institute of Computing Technology (ICT) of the Chinese Academy of Sciences may be licensed or sold to various customers or licensees, such as Texas Instruments, Qualcomm, Apple, or Samsung and implemented in processors produced by these customers or licensees. 
       FIG. 11  shows a block diagram illustrating the development of IP cores according to one embodiment. Storage  1130  includes simulation software  1120  and/or hardware or software model  1110 . In one embodiment, the data representing the IP core design can be provided to the storage  1130  via memory  1140  (e.g., hard disk), wired connection (e.g., internet)  1150  or wireless connection  1160 . The IP core information generated by the simulation tool and model can then be transmitted to a fabrication facility where it can be fabricated by a third party to perform at least one instruction in accordance with at least one embodiment. 
     In some embodiments, one or more instructions may correspond to a first type or architecture (e.g., x86) and be translated or emulated on a processor of a different type or architecture (e.g., ARM). An instruction, according to one embodiment, may therefore be performed on any processor or processor type, including ARM, x86, MIPS, a GPU, or other processor type or architecture. 
       FIG. 12  illustrates how an instruction of a first type is emulated by a processor of a different type, according to one embodiment. In  FIG. 12 , program  1205  contains some instructions that may perform the same or substantially the same function as an instruction according to one embodiment. However the instructions of program  1205  may be of a type and/or format that is different or incompatible with processor  1215 , meaning the instructions of the type in program  1205  may not be able to be executed natively by the processor  1215 . However, with the help of emulation logic,  1210 , the instructions of program  1205  are translated into instructions that are natively capable of being executed by the processor  1215 . In one embodiment, the emulation logic is embodied in hardware. In another embodiment, the emulation logic is embodied in a tangible, machine-readable medium containing software to translate instructions of the type in the program  1205  into the type natively executable by the processor  1215 . In other embodiments, emulation logic is a combination of fixed-function or programmable hardware and a program stored on a tangible, machine-readable medium. In one embodiment, the processor contains the emulation logic, whereas in other embodiments, the emulation logic exists outside of the processor and is provided by a third party. In one embodiment, the processor is capable of loading the emulation logic embodied in a tangible, machine-readable medium containing software by executing microcode or firmware contained in or associated with the processor. 
       FIG. 13  is a block diagram contrasting the use of a software instruction converter to convert binary instructions in a source instruction set to binary instructions in a target instruction set according to embodiments of the invention. In the illustrated embodiment, the instruction converter is a software instruction converter, although alternatively the instruction converter may be implemented in software, firmware, hardware, or various combinations thereof.  FIG. 13  shows a program in a high level language  1302  may be compiled using an x86 compiler  1304  to generate x86 binary code  1306  that may be natively executed by a processor with at least one x86 instruction set core  1316 . The processor with at least one x86 instruction set core  1316  represents any processor that can perform substantially the same functions as a Intel processor with at least one x86 instruction set core by compatibly executing or otherwise processing (1) a substantial portion of the instruction set of the Intel x86 instruction set core or (2) object code versions of applications or other software targeted to run on an Intel processor with at least one x86 instruction set core, in order to achieve substantially the same result as an Intel processor with at least one x86 instruction set core. The x86 compiler  1304  represents a compiler that is operable to generate x86 binary code  1306  (e.g., object code) that can, with or without additional linkage processing, be executed on the processor with at least one x86 instruction set core  1316 . Similarly,  FIG. 13  shows the program in the high level language  1302  may be compiled using an alternative instruction set compiler  1308  to generate alternative instruction set binary code  1310  that may be natively executed by a processor without at least one x86 instruction set core  1314  (e.g., a processor with cores that execute the MIPS instruction set of MIPS Technologies of Sunnyvale, Calif. and/or that execute the ARM instruction set of ARM Holdings of Sunnyvale, Calif.). The instruction converter  1312  is used to convert the x86 binary code  1306  into code that may be natively executed by the processor without an x86 instruction set core  1314 . This converted code is not likely to be the same as the alternative instruction set binary code  1310  because an instruction converter capable of this is difficult to make; however, the converted code will accomplish the general operation and be made up of instructions from the alternative instruction set. Thus, the instruction converter  1312  represents software, firmware, hardware, or a combination thereof that, through emulation, simulation or any other process, allows a processor or other electronic device that does not have an x86 instruction set processor or core to execute the x86 binary code  1306 . 
       FIG. 14A  illustrates a flow diagram for one embodiment of an example process for using an instruction to provide SIMD vector leading zero count functionality useful for generating permute controls for efficient vector address conflict resolution. Process  1401  and other processes herein disclosed are performed by processing blocks that may comprise dedicated hardware or software or firmware operation codes executable by general purpose machines or by special purpose machines or by a combination of both. 
     In processing block  1410  of process  1401  the set of indices is initialized, e.g. to the values 7, 2, 7, 1 and 7. It will be appreciated that the number of offset indices and the values of the offset indices is intended to be illustrative and not restrictive of embodiments of the invention. In particular, the number of offset indices in a register may be determined by the particular application and/or the size of data elements corresponding to the indices. The example values of offset indices are simply intended to illustrate resolution of dependency conflicts. In processing block  1415  the elements left mask is set to all (e.g. five) ones. In processing block  1420  the dependencies masks are set according to a prior techniques of process  1405  to reflect all matching offset indices. Then in processing block  1425  a set of order masks is initialized. In processing block  1430  the conflict masks are computed by performing a bitwise AND between the dependencies masks and the order masks. While the prior technique of process  1405  is illustrated, in contrast, it will be appreciated that an improvement on process  1405  for generating the conflict masks in processing block  1430 , but directly as the result of one SIMD vector conflict detection instruction, will be described in more detail below starting with  FIG. 14B . 
     Proceeding next to processing block  1439 , the leading zero counts are computed using a vector packed leading zero count instruction, VPLZCNT, on the conflict masks by counting the number of most significant contiguous bits that are set to zero for each data field of the conflict masks and storing each count as a value in a corresponding data field of the leading zero counts. In processing block  1440  the maximum counts are initialized to all fours, which is a value one less than the number of bits used to represent a conflict mask in the example illustrated. In processing block  1445  a set of permute indices is computed by performing a SIMD packed subtraction, PSUB, subtracting the value of each leading zero count from a corresponding maximum count value, one less than the number of bits used to represent a conflict mask, to generate a corresponding difference of the maximum counts minus the leading zero counts. It will be appreciated that those locations corresponding to offset indices that are not dependent on a prior computation have permute indices of negative one, which may also be used advantageously. 
     In processing block  1450  data is gathered from memory and modified values are computed according to the offset indices and an elements left mask which is (optionally) all ones. Next in processing block  1455  the elements left mask is recomputed using a packed compare not equal instruction, PCMPNEQ, comparing the permute indices advantageously with all negative ones. In processing block  1460  a determination is made whether the elements left mask is zero (0). If so in processing block  1465  the data is scattered to memory using the offset indices, and the processing of this set of SIMD data ends in processing block  1499 . 
     Otherwise in processing block  1470  the data is permuted by performing a SIMD vector packed permutation, VPERM, employing the permute indices and the elements left mask as a completion mask to advantageously update only the elements left to process. In processing block  1475  the required computations are performed on the data elements left to process using the elements left mask as a completion mask. Then in a prior technique process  1406  a set of conflicted out elements is initialized by broadcasting the elements left mask to all elements in processing block  1480 . Then the set of conflict masks is recomputed using a vector packed AND instruction on the previous conflict masks and the new conflicted out elements. The new elements left mask is then computed using a packed compare not equal instruction, PCMPNEQ, comparing each conflict mask with all zeroes. Processing then reiterates beginning in processing block  1460  with the testing of a new elements left mask. While the prior technique of process  1406  is illustrated, in contrast, it will be appreciated that an improvement on process  1406  for generating the elements left mask of processing block  1490  by using instead, an iteration count, the result of a SIMD vector population count instruction, will also be described below starting with  FIG. 14C . 
     It will be appreciated that SIMD vector leading zero count instructions, as in the embodiments described herein, may be used advantageously with variable sized elements and conflict masks to provide SIMD permute controls, thereby permitting more efficient SIMD address conflict resolution in registers without performing dependent computations through memory. 
       FIG. 14B  illustrates a flow diagram for one embodiment of an example of using an instruction to provide SIMD vector address conflict detection functionality. In processing block  1410  of process  1402  the set of offset indices is initialized, e.g. to the values 7, 2, 7, 1 and 7. It will again be appreciated that the number of offset indices and the values of the offset indices is intended to be illustrative and not restrictive of embodiments of the invention. In particular, the number of offset indices in a register may be determined by the particular application and/or the size of data elements corresponding to the indices. The example values of offset indices are simply intended to illustrate resolution of dependency conflicts. In processing block  1415  the elements left mask is set to all (e.g. five) ones. 
     In processing block  1431  the conflict masks are computed using a SIMD vector packed conflict instruction, VPCONFLICT, comparing an offset in each element of the set of offset indices with an offset in every less significant element to determine if they hold matching offset. It will be appreciated that processing block  1431  represents a notable improvement on the prior technique of process  1405 . 
     In processing block  1450  data is gathered from memory and modified values are computed according to the offset indices and an elements left mask which is (optionally) all ones. Next in the prior technique process  1406  a set of conflicted out elements is initialized by broadcasting the elements left mask to all elements in processing block  1480 . Then in processing block  1485  the set of conflict masks is recomputed using a vector packed AND instruction on the previous conflict masks and the new conflicted out elements. Then the new elements left mask is computed in processing block  1490  using a packed compare not equal instruction, PCMPNEQ, comparing each conflict mask with all zeroes. In processing block  1462  the elements left mask are negated to form a did these mask, and the data elements are scattered in processing block  1466  to memory according to the offset indices. In processing block  1460  a determination is made whether the elements left mask is zero (0). If so in processing of this set of SIMD data ends in processing block  1499 . Otherwise processing reiterates beginning in processing block  1450  of process  1402 . 
     It will be appreciated that SIMD vector address conflict detection instructions, as in the embodiments described herein, may be used for variable sized elements and memory offsets to provide SIMD vector address conflict detection functionality and to generate conflict masks for efficient SIMD address conflict resolution. It will also be appreciated that SIMD vector address conflict detection instructions may be used in combination with SIMD vector leading zero count instructions, as in the embodiments described herein, to provide SIMD permute controls, for more efficient SIMD address conflict resolution especially in certain gather-modify-scatter applications permitting address conflict resolution in registers without performing dependent computations through memory. 
       FIG. 14C  illustrates a flow diagram for one embodiment of an example of using an instruction to provide SIMD vector address conflict detection functionality. In processing block  1410  of process  1403  the set of offset indices is once again initialized, e.g. to the values 7, 2, 7, 1 and 7. In processing block  1431  the conflict masks are computed using a SIMD vector packed conflict instruction, VPCONFLICT, comparing an offset in each element of the set of offset indices with an offset in every less significant element to determine if they hold matching offset. 
     In processing block  1432 , the iteration counts are computed using a SIMD vector population count instruction, VPOPCNT, counting a number of bits set to one for each data field of the conflict masks and storing each count as a value in a corresponding data field of the iteration counts. Then a mask is computed in processing block  1433  using a vector packed compare greater than instruction, VPCMPGT, comparing each iteration count with a corresponding threshold value to test if any of the dependencies would require too many iterations. In processing block  1434 , it is determined if all of the tests comparing iteration counts to the thresholds were negative, resulting in zeroes. If not then in processing block  1436  a scalar processing version of the computations is performed for these elements because there are too many serial dependencies. 
     Otherwise, a zero test result indicates that the dependencies may be resolve in a SIMD fashion without too many iterations, and so processing proceeds to processing block  1446  where the elements left mask is initialized to all ones. The elements of an increment vector are initialized, all to values of one in processing block  1447 , and an iteration vector is initialized to zeroes in processing block  1448 . 
     In processing block  1449  a mask, do_these, of which elements are ready to process is computed using a packed compare for equality instruction, PCMPEQ, comparing each iteration count with the current iteration vector. In processing block  1450  data is gathered from memory and modified values are computed according to the offset indices and the completion mask, do_these, of which elements to process. Then an elements left mask is computed in processing block  1451  using a vector packed compare greater than instruction, VPCMPGT, comparing each iteration count with the current iteration vector. It will be appreciated that processing block  1451  represents an improvement on the prior technique of process  1406 . In processing block  1458  the processed data elements are scattered back to memory according to the offset indices and the completion mask, do_these, and the processing proceeds to processing block  1460  where a determination is made if the elements left mask is zero, indicating that no elements are left to process. If so processing of this set of SIMD data ends in processing block  1499 . Otherwise processing proceeds to processing block  1463  where the iteration vector is incremented by a packed addition, PADD, of the increment vector to the current iteration vector. Then processing reiterates beginning in processing block  1449  of process  1403 . It will be appreciated that SIMD vector population count instructions, as in the embodiments described herein, may be used with variable sized elements and conflict masks to efficiently compute iteration counts and to provide SIMD completion masks for iterations of a SIMD address conflict resolution. 
       FIG. 14D  illustrates a flow diagram for an alternative embodiment of an example of using the combined instructions, for SIMD vector packed conflict detection, SIMD vector packed population counts, and SIMD vector packed leading zero counts to provide efficient SIMD vector address conflict resolution. In processing block  1410  of process  1404  the set of offset indices is once again initialized, e.g. to the values 7, 2, 7, 1 and 7. In processing block  1431  the conflict masks are computed using the SIMD vector packed conflict instruction, VPCONFLICT, comparing an offset in each element of the set of offset indices with an offset in every less significant element to determine if they hold matching offset. In processing block  1432 , the iteration counts are computed using the SIMD vector population count instruction, VPOPCNT, counting a number of bits set to one for each data field of the conflict masks and storing each count as a value in a corresponding data field of the iteration counts. Then an elements left mask is computed in processing block  1437  using a vector packed compare greater than instruction, VPCMPGT, comparing each iteration count with a vector of all zeroes. In processing block  1438  a determination is made whether or not the elements left mask is zero, indicating that there are no dependencies to resolve, in which case processing proceeds directly to processing blocks  1452 ,  1460 ,  1465  and  1499 , where the data elements may be processed without any dependency resolution. 
     Otherwise, if the elements left mask is not zero in processing block  1438 , then processing proceeds to processing block  1439  where the leading zero counts are computed using a vector packed leading zero count instruction, VPLZCNT, on the conflict masks by counting the number of most significant contiguous bits that are set to zero for each data field of the conflict masks and storing each count as a value in a corresponding data field of the leading zero counts. In processing block  1440  the maximum counts are initialized to all fours, which in this example, is a value of one less than the number of bits used to represent a conflict mask. In processing block  1445  a set of permute indices is computed by performing a SIMD packed subtraction, PSUB, subtracting the value of each leading zero count from a corresponding maximum count value, one less than the number of bits used to represent a conflict mask, to generate a corresponding difference of the maximum counts minus the leading zero counts. One will be reminded that those locations corresponding to offset indices that are not dependent on a prior computation have permute indices of negative one, which may be used advantageously. 
     The elements of an increment vector are initialized, all to values of one in processing block  1447 , and an iteration vector is initialized to zeroes in processing block  1448 . In processing block  1452  data is gathered from memory and modified values are computed according to the offset indices and the optional completion mask of all ones. It will be appreciated that any incorrectly modified data values will be subsequently resolved 
     In processing block  1460  a determination is made if the elements left mask is zero, indicating that no elements are left to process. If so in processing block  1465  the processed data elements are scattered back to memory according to the offset indices and the processing proceeds to processing block  1499  where processing of this set of SIMD data ends. It will be appreciated that the scatter operation will store the latest updated value to any one memory location thereby correctly resolving any conflict dependencies. 
     Otherwise if the elements left mask is not zero in processing block  1460 , then processing proceeds to processing block  1463  where the iteration vector is incremented by a packed addition, PADD, of the increment vector to the current iteration vector. In processing block  1464  a mask, do_these, of which elements are ready to process is computed using a packed compare for equality instruction, PCMPEQ, comparing each iteration count with the newly computed iteration vector. In processing block  1470  the data is permuted by performing a SIMD vector packed permutation, VPERM, employing the permute indices and the do_these mask as a completion mask to advantageously update only the elements to process in this iteration. In processing block  1475  the required computations are performed on the data elements to process in this iteration using the do_these mask as a completion mask. An elements left mask is computed in processing block  1476  using a vector packed compare greater than instruction, VPCMPGT, comparing each iteration count with the current iteration vector. Then processing reiterates beginning in processing block  1460  of process  1404 . It will be appreciated that the combination of instructions and logic disclosed herein, for SIMD vector packed conflict detection, SIMD vector packed population counts, and SIMD vector packed leading zero counts, provide for more efficient SIMD address conflict resolution especially in certain gather-modify-scatter applications. 
       FIG. 15A  illustrates a flow diagram for one embodiment of a process to provide SIMD permute controls for efficient vector address conflict resolution with leading zero count functionality. Process  1501  and other processes herein disclosed are performed by processing blocks that may comprise dedicated hardware or software or firmware operation codes executable by general purpose machines or by special purpose machines or by a combination of both. 
     In processing block  1535  of process  1501  the number of most significant contiguous bits that are set to zero are counted for each element of a first vector register. In processing block  1540  each count is stored as a value in a corresponding data field of a first vector destination register. In processing block  1545  the value of each of the data fields in the first vector destination register are subtracted from a corresponding value, one less than the number of bits used to store the elements in the first vector register to generate a corresponding difference. In processing block  1550  each of the corresponding differences is stored as a permute control value in a corresponding data field of a second vector destination register. In processing block  1555  the values of each of the data fields in the second vector destination register are compared with a corresponding copy of a specific value (e.g. such as negative one, or some other value) in each of the data fields in a vector register to detect elements ready to process, and in processing block  1560  the comparison results are stored as a corresponding mask value in a vector completion mask indicating next elements ready to process, the vector mask to be used along with the set of permute control values. In processing block  1565 , the SIMD computation is performed and in processing block  1580  the SIMD data is permuted using the permute control values and the completion mask to prepare the input data for the next elements to process. In processing block  1595  a determination is made whether or not processing of all the elements is finished, and if so processing of these elements ends in processing block  1599 . Otherwise, in processing block  1586  a logical AND of each element of the first vector source is performed with a copy of the completion mask and processing reiterates beginning in processing block  1535 . It will be appreciated that while process  1501 , as illustrated, does not presume that the processed elements need to be stored to memory, any such storing, or scattering to memory, together with additional subsequent iterations of process  1501  may be performed in accordance with alternative embodiments of the invention. 
       FIG. 15B  illustrates a flow diagram for one embodiment of a process  1502  to provide SIMD vector address conflict detection functionality. 
     In processing block  1505  an offset in each element of a first register or memory vector source is compared with an offset in every less significant element of the vector source to determine if they hold matching offsets. In processing block  1510  any mask bits corresponding to less significant elements in the first vector source holding offsets matching the offset in the element corresponding to a mask in a first vector destination are set to one. Any other bits in the destination register are set to a second value (e.g. zero) in processing block  1511 . 
     In processing block  1516  the values of each of the masks stored in the first destination register are compared with a corresponding copy of a specific value (e.g. of zero) in another vector, in order to generate a mask of the elements that depend upon computations of less significant elements. In processing block  1572  the mask of elements that depend upon incomplete computations on less significant elements is used to detect elements ready to process and generate a completion mask. In processing block  1564  the SIMD computation is performed on the data using the completion mask. Then in processing block  1569  the mask of elements that depend upon incomplete computations on less significant elements is updated. A determination is made in processing block  1595  whether or not processing of all the elements is finished, and if so processing of these elements ends in processing block  1599 . Otherwise, processing reiterates beginning in processing block  1572 . It will also be appreciated that while process  1502 , as illustrated, does not presume that the processed elements need to be stored to memory, any such storing, or scattering to memory, together with additional subsequent iterations of process  1502  may be performed in accordance with alternative embodiments of the invention. 
       FIG. 15C  illustrates a flow diagram for one embodiment of a process  1503  to provide SIMD vector address conflict detection functionality. In processing block  1515  the number of bits set to one is counted for each element in a first vector source, each element storing the same variable number of bits according to particular population count instruction. In processing block  1520  the counts are stored as a value in a corresponding element in a first vector destination. In processing block  1525  the counts in the first destination register are compared, each with a corresponding value in a second vector source, in order to determine if they exceed a threshold value and to generate corresponding mask values that, in processing block  1530 , are stored according to the comparison results in a first vector mask destination. In processing block  1570  the counts in the first destination register are compared, each with a corresponding value in a third vector source, in order to determine the corresponding elements in a fourth vector source on which to operate in a current iteration. The comparison results are stored in processing block  1575  as mask values in a completion mask to be used to perform a SIMD operation. A determination is made in processing block  1577  whether or not processing of all the elements is finished, and if so processing of these elements ends in processing block  1599 . Otherwise processing proceeds to processing block  1563  where one or more SIMD operation is performed using the completion mask. Then in processing block  1568  the iteration count is updated and processing reiterates beginning in processing block  1570 . It will again be appreciated that while process  1503 , as illustrated, does not presume that the processed elements need to be stored to memory, any such storing, or scattering to memory, together with additional subsequent iterations of process  1503  may be performed in accordance with alternative embodiments of the invention. 
       FIG. 15D  illustrates a flow diagram for an alternative embodiment of a combined process  1504  to provide efficient SIMD vector address conflict resolution. In processing block  1505  an offset in each element of a first register or memory vector source is compared with an offset in every less significant element of the first vector source to determine if they hold matching offsets. In processing block  1510  mask bits are set to one according to matching offsets in less significant elements, for masks in a first vector destination corresponding to each element of the first vector source. In processing block  1515  the number of bits set to one are counted for each element of the first vector destination, and in processing block  1520  the counts are stored in a second vector destination. In processing block  1526  the counts in the second destination register are compared, each with a corresponding value in a second vector source, in order to determine the corresponding elements in a third vector source on which to perform a SIMD operation. The comparison results are stored in processing block  1531  as mask values in a first vector mask destination. In processing block  1533  a determination is made whether or not there are dependencies in the SIMD operation. If not processing may proceed directly to processing block  1553 . Otherwise processing proceeds first to processing block  1535  where the number of most significant contiguous bits set to zero are counted for each element of the first vector destination. In processing block  1540  each count is stored as a value in a corresponding data field of a third vector destination. In processing block  1545  the counts of each of the data fields in the third vector destination register are subtracted from a corresponding value, one less than the number of bits used to store the elements in the first vector destination to generate a corresponding difference. In processing block  1550  each of the corresponding differences is stored as a permute control value in a corresponding data field of a fourth vector destination. 
     Then in processing block  1553  elements are gathered from memory or cache into the third vector source using the offsets in the first vector source and the first vector mask destination as a completion mask. In processing block  1566  one or more SIMD operations are performed on the elements of the third vector source using the first vector mask destination as a completion mask. A determination is made in processing block  1567  whether or not processing of all the data elements is finished. If so in processing block  1590  the data elements of the third vector source are scattered back to memory or cache using the offsets in the first vector source, and processing of these elements ends in processing block  1599 . 
     Otherwise, in processing block  1568  the iteration count is updated. Then in processing block  1571  the counts in the second vector destination are compared, each with the iteration count to determine the elements on which to operate next. In processing block  1576  the comparison results are stored as mask values in the first mask destination completion mask. In processing block  1581  elements in the third vector source are permuted using permute controls in the fourth vector destination and the first mask destination completion mask. Then in processing block  1585  the counts in the second vector destination are compared to the iteration count to determine if this iteration can be identified as the last iteration. Processing then reiterates beginning in processing block  1566 . Thus the combination of instructions and logic disclosed herein provide for more efficient SIMD address conflict resolution especially in certain gather-modify-scatter applications. 
       FIG. 16  illustrates an embodiment of an apparatus  1601  for executing an instruction to provide SIMD vector leading zero count functionality useful for generating permute controls for efficient vector address conflict resolution. Embodiments of apparatus  1601  may be part of a pipeline  400  (e.g. execution stage  416 ) or part of a core  490  (e.g. execution unit(s)  462 ) for execution of an instruction to provide SIMD vector leading zero count functionality. Embodiments of apparatus  1601  may be coupled with a decode stage (e.g. decode  406 ) or a decoder (e.g. decode unit  440 ) to decode an instruction for a SIMD vector leading zero count, which may permit efficient vector address conflict resolution. One or more execution units (e.g. execution apparatus  1601 ) responsive to the decoded instruction, read the plurality of bits of each of the data fields in memory vector operand or vector register  1610  or  1620 , and for each data field of the memory vector operand or vector register  1610  or  1620 , count the number of most significant contiguous bits set to zero, and store the count as a value in a corresponding data field of a SIMD destination register  1650  or  1660 . 
     For example, embodiments of apparatus  1601  may be coupled with vector registers (e.g. physical register files unit(s)  458 ) comprising a variable plurality of n variable sized data fields to store values of a variable plurality of n variable sized data elements. Embodiments of the instruction to provide SIMD vector leading zero count functionality specify a vector leading zero count operation and a data field size for performing the SIMD leading zero count for each data field of the memory vector operand or vector register, e.g.  1610  or  1620 , and storing the counts as values in corresponding data fields of the specified size in the SIMD destination register, e.g.  1650  or  1660 . 
     For example, one embodiment of apparatus  1601  for executing an instruction to provide SIMD vector leading zero count functionality reads the plurality of bits of each of the data fields of a first size (e.g. 16-bits or 32-bits) in memory vector operand or vector register  1620 , and counts the number of most significant contiguous bits set to zero in leading zero counters  1630 - 1637  of a leading zero count circuit  1603 , then stores the counts as values in corresponding data fields of the same specified size in the SIMD destination register  1660 . Another embodiment of apparatus  1601  for executing an instruction to provide a SIMD vector leading zero count reads the plurality of bits of each of the data fields of a second size (e.g. 32-bits or 64-bits) in a memory vector operand or vector register  1610 , and selects the counts of the most significant contiguous bits set to zero from odd leading zero counters  1631  to  1637 , or adds a value m to the counts from even leading zero counters  1630  to  1636 , respectively, in selective adder circuits  1640  to  1643  of a leading zero count combination circuit  1604 , then stores the combined counts as values in corresponding data fields of the specified size in the SIMD destination register  1650 . It will be appreciated that alternative embodiments of apparatus  1601  for executing an instruction to provide SIMD vector leading zero counts may be capable of performing both SIMD vector leading zero counts of a first data field size and SIMD vector leading zero counts of a second data field size as shown in  FIG. 16 , or may be modified to perform SIMD vector leading zero counts for a variety of specified data field sizes. SIMD vector leading zero count instructions, as in the embodiments described herein, may be used with variable sized elements and conflict masks to provide SIMD permute controls, thereby permitting more efficient SIMD address conflict resolution in registers without performing dependent computations through memory. Thus the SIMD vector leading zero count instructions and logic disclosed herein provide for more efficient SIMD address conflict resolution especially in certain gather-modify-scatter applications, for example as discussed with regard to  FIGS. 14A and 14D . 
       FIG. 17  illustrates an embodiment of an apparatus  1701  for executing an instruction to provide SIMD vector address conflict detection functionality for efficient vector address conflict resolution. Embodiments of apparatus  1701  may also be part of a pipeline  400  (e.g. execution stage  416 ) or part of a core  490  (e.g. execution unit(s)  462 ) for execution of an instruction to provide SIMD vector address conflict detection functionality. Embodiments of apparatus  1701  may be coupled with a decode stage (e.g. decode  406 ) or a decoder (e.g. decode unit  440 ) to decode an instruction for a SIMD vector address conflict detection, which may permit efficient vector address conflict resolution. One or more execution units (e.g. execution apparatus  1701 ) responsive to the decoded instruction, read the values of each of the data fields in memory vector operand or vector register  1710  or  1720 , and for each data field of the memory vector operand or vector register  1710  or  1720 , compares its corresponding offset with every less significant data field of the memory vector operand or vector register to determine if they hold matching offsets. Then for each data field in a SIMD destination register  1750  or  1760  corresponding to an offset in the memory vector operand or vector register  1710  or  1720 , execution apparatus  1701  sets (e.g. to one) any mask bits corresponding to less significant data fields holding a matching, and set any other bits in the SIMD destination register  1750  or  1760  to a different value (e.g. like zero). 
     For example, embodiments of apparatus  1701  may be coupled with vector registers (e.g. physical register files unit(s)  458 ) comprising a variable plurality of n variable sized data fields to store values of a variable plurality of n variable sized data elements. Embodiments of the instruction to provide SIMD vector address conflict detection functionality specify a vector address conflict detection operation and a data field size for performing the SIMD address conflict detection for each data field of the memory vector operand or vector register, e.g.  1710  or  1720 , and storing the conflict masks in corresponding data fields of the specified size in the SIMD destination register, e.g.  1750  or  1760 . 
     For example, one embodiment of apparatus  1701  for executing an instruction to provide SIMD vector address conflict detection functionality reads the values of each of the data fields of a first size (e.g. 16-bits or 32-bits) in memory vector operand or vector register  1720 , and compares its corresponding offset with the offset in every less significant data field for equality using equality comparators, e.g. equality comparators  1730 - 1736 , of an address conflict detection circuit  1703 , then stores the conflict masks in corresponding data fields of the same specified size in the SIMD destination register  1760 . Another embodiment of apparatus  1701  for executing an instruction to provide a SIMD vector address conflict detection reads the values of each of the data fields of a second size (e.g. 32-bits or 64-bits) in a memory vector operand or vector register  1610 , and combines (e.g. ANDs together) comparisons of corresponding adjacent data subfields, e.g. from equality comparators  1732  and  1733 ,  1730  and  1736 ,  1734  and  1735 , etc., respectively, in AND logic  1740  to  1742  of a conflict combination circuit  1704 , then stores the combined conflict masks in corresponding data fields of the specified size in the SIMD destination register  1750 . It will be appreciated that alternative embodiments of apparatus  1701  for executing an instruction to provide SIMD vector address conflict detection may be capable of performing both SIMD vector address conflict detection of a first data field size and SIMD vector address conflict detection of a second data field size as shown in  FIG. 17 , or may be modified to perform SIMD vector address conflict detection for a variety of specified data field sizes. It will be appreciated that SIMD vector address conflict detection instructions, as in the embodiments described herein, may be used for variable sized elements and memory offsets to provide SIMD vector address conflict detection functionality and to generate conflict masks for efficient SIMD address conflict resolution. It will also be appreciated that SIMD vector address conflict detection instructions may be used in combination with SIMD vector leading zero count instructions, as in the embodiments described herein, to provide SIMD permute controls, for more efficient SIMD address conflict resolution especially in certain gather-modify-scatter applications, for example as discussed with regard to  FIGS. 14A, 14B and 14D . 
       FIG. 18  illustrates an embodiment of an apparatus  1801  for executing an instruction to provide SIMD vector population count functionality for efficient vector address conflict resolution. Embodiments of apparatus  1801  may be part of a pipeline  400  (e.g. execution stage  416 ) or part of a core  490  (e.g. execution unit(s)  462 ) for execution of an instruction to provide SIMD population count functionality. Embodiments of apparatus  1801  may be coupled with a decode stage (e.g. decode  406 ) or a decoder (e.g. decode unit  440 ) to decode an instruction for a SIMD population count, which may permit efficient vector address conflict resolution. One or more execution units (e.g. execution apparatus  1801 ) responsive to the decoded instruction, read the plurality of bits of each of the data fields in memory vector operand or vector register  1810  or  1820 , and for each data field of the memory vector operand or vector register  1810  or  1820 , count the number of bits set to one, and store the count as a value in a corresponding data field of a SIMD destination register  1850  or  1860 . 
     For example, embodiments of apparatus  1801  may be coupled with vector registers (e.g. physical register files unit(s)  458 ) comprising a variable plurality of n variable sized data fields to store values of a variable plurality of n variable sized data elements. Embodiments of the instruction to provide SIMD population count functionality specify a vector population count operation and a data field size for performing the SIMD population count for each data field of the memory vector operand or vector register, e.g.  1810  or  1820 , and storing the counts as values in corresponding data fields of the specified size in the SIMD destination register, e.g.  1850  or  1860 . 
     For example, one embodiment of apparatus  1801  for executing an instruction to provide SIMD vector population count functionality reads the plurality of bits of each of the data fields of a first size (e.g. 16-bits or 32-bits) in memory vector operand or vector register  1820 , and counts the number of bits set to one in population counters  1830 - 1837  of a population count circuit  1803 , then stores the counts as values in corresponding data fields of the same specified size in the SIMD destination register  1860 . Another embodiment of apparatus  1801  for executing an instruction to provide a SIMD vector population count reads the plurality of bits of each of the data fields of a second size (e.g. 32-bits or 64-bits) in a memory vector operand or vector register  1810 , and adds the counts of the bits set to one from population counters  1830 - 1831 , to  1836 - 1837 , respectively, in adders  1840  to  1845  of a population count combination circuit  1804 , then stores the combined counts as values in corresponding data fields of the specified size in the SIMD destination register  1850 . It will be appreciated that alternative embodiments of apparatus  1801  for executing an instruction to provide SIMD vector population counts may be capable of performing both SIMD vector population counts of a first data field size and SIMD vector population counts of a second data field size as shown in  FIG. 18 , or may be modified to perform SIMD vector population counts for a variety of specified data field sizes. SIMD vector population count instructions, as in the embodiments described herein, may be used with variable sized elements and conflict masks to efficiently compute iteration counts and to provide SIMD completion masks for iterations of a SIMD address conflict resolution. Thus the combination of instructions and logic disclosed herein provide for more efficient SIMD address conflict resolution especially in certain gather-modify-scatter applications, for example as discussed with regard to  FIGS. 14A-14D . 
     Embodiments of the mechanisms disclosed herein may be implemented in hardware, software, firmware, or a combination of such implementation approaches. Embodiments of the invention may be implemented as computer programs or program code executing on programmable systems comprising at least one processor, a storage system (including volatile and non-volatile memory and/or storage elements), at least one input device, and at least one output device. 
     Program code may be applied to input instructions to perform the functions described herein and generate output information. The output information may be applied to one or more output devices, in known fashion. For purposes of this application, a processing system includes any system that has a processor, such as, for example; a digital signal processor (DSP), a microcontroller, an application specific integrated circuit (ASIC), or a microprocessor. 
     The program code may be implemented in a high level procedural or object oriented programming language to communicate with a processing system. The program code may also be implemented in assembly or machine language, if desired. In fact, the mechanisms described herein are not limited in scope to any particular programming language. In any case, the language may be a compiled or interpreted language. 
     One or more aspects of at least one embodiment may be implemented by representative instructions stored on a machine-readable medium which represents various logic within the processor, which when read by a machine causes the machine to fabricate logic to perform the techniques described herein. Such representations, known as “IP cores” may be stored on a tangible, machine readable medium and supplied to various customers or manufacturing facilities to load into the fabrication machines that actually make the logic or processor. 
     Such machine-readable storage media may include, without limitation, non-transitory, tangible arrangements of articles manufactured or formed by a machine or device, including storage media such as hard disks, any other type of disk including floppy disks, optical disks, compact disk read-only memories (CD-ROMs), compact disk rewritable&#39;s (CD-RWs), and magneto-optical disks, semiconductor devices such as read-only memories (ROMs), random access memories (RAMs) such as dynamic random access memories (DRAMs), static random access memories (SRAMs), erasable programmable read-only memories (EPROMs), flash memories, electrically erasable programmable read-only memories (EEPROMs), magnetic or optical cards, or any other type of media suitable for storing electronic instructions. 
     Accordingly, embodiments of the invention also include non-transitory, tangible machine-readable media containing instructions or containing design data, such as Hardware Description Language (HDL), which defines structures, circuits, apparatuses, processors and/or system features described herein. Such embodiments may also be referred to as program products. 
     In some cases, an instruction converter may be used to convert an instruction from a source instruction set to a target instruction set. For example, the instruction converter may translate (e.g., using static binary translation, dynamic binary translation including dynamic compilation), morph, emulate, or otherwise convert an instruction to one or more other instructions to be processed by the core. The instruction converter may be implemented in software, hardware, firmware, or a combination thereof. The instruction converter may be on processor, off processor, or part on and part off processor. 
     Thus, techniques for performing one or more instructions according to at least one embodiment are disclosed. While certain exemplary embodiments have been described and shown in the accompanying drawings, it is to be understood that such embodiments are merely illustrative of and not restrictive on the broad invention, and that this invention not be limited to the specific constructions and arrangements shown and described, since various other modifications may occur to those ordinarily skilled in the art upon studying this disclosure. In an area of technology such as this, where growth is fast and further advancements are not easily foreseen, the disclosed embodiments may be readily modifiable in arrangement and detail as facilitated by enabling technological advancements without departing from the principles of the present disclosure or the scope of the accompanying claims.