Digital Filtering with SIMD-processor

Abstract: A single-instruction multiple-data processor (10) has an input layer especially designed for high data input and output rates. The processor (10) has a number of processing elements (20), each corresponding to incoming data samples. The processing elements (20) are interleaved so that a set of samples can be input in parallel. This configuration is especially useful for scan rate conversation, where the data output rate may not necessarily be the same as the data input rate. The processor (10) is also programmable, which makes it especially useful for digital filtering. Near-neighbor communications among processing elements (20) realize the delays required for horizontal filtering.

Description: TECHNICAL FIELD OF THE INVENTION This invention generally relates to single instruction, multiple data processors, and more particularly to a such a processor that is programmable and achieves a high processing throughput speed. BACKGROUND OF THE INVENTION Single-instruction multiple-data (SIMD) processors are characterized by having an array of processors that perform the same operation simultaneously on every element of a data array. Vector processing, an application of SIMD processors, uses vector instructions, which specify the operation to be performed and specify the list of operands, i.e., the data vector, on which it will operate. The use of processor arrays and vector processing can result in extensive parallelism, resulting in high execution speeds. Yet, despite impressive execution speeds, getting data in and out of the processor can be a problem. Execution speeds are less useful if input/output speeds cannot keep up. In many applications, such as video processing, real-time processing speed is desirable. Yet, a stumbling block to real-time processing is the large amount of data that must be processed to generate the pixels, lines, and frames of a video picture. A need exists for an easily manufactured SIMD processor that maximizes data input rates without increasing manufacturing costs. Although the need for such processors is not limited to television, digital television processing involves processing tasks, such as scan rate conversion and various filtering processes, for which a processor with a fast throughput is desirable. With regard to scan rates, television relies on the concept that a picture can be broken down into a mosaic suitable for transmitting and then reassembled to produce a television picture. This process is accomplished with linear scanning. The television picture is scanned in a sequential series of horizontal lines, at both the transmitting and receiving end of the television system. Various geopolitical regions have different scanning standards. The United States uses the National Television Systems Committee (NTSC) standard. Each picture, i.e., frame, has 525 lines. These lines are interlaced to make two fields having 262.5 lines each, and each field is scanned at a rate of 60 fields per second. Some countries use a Phase Alternate Line (PAL) system, which has similar characteristics. Other countries use a Sequential Color and Memory (SECAM) system, in which 625 lines make up a frame. The lines are interlaced to make two fields having 312.5 lines each, and each field is scanned at a rate of 50 fields per second. If a scan rate is too slow, the viewer will notice a large area flicker. The 60 Hz and 50 Hz standard scan rates are intended to exceed a rate at which flicker is annoyingly noticeable, but not place expensive technological demands on the receiving system. Nevertheless, faster scan rates are desirable for improved viewing. In addition to scan rates, another factor in picture quality is the number of lines per frame, i.e., vertical resolution. If there are too few lines, the distinction between each line is perceptible. Like scan rate standards, the selection of a standard number of lines per field is intended to surpass the viewer's annoyance level without unduly burdensome technological costs. Yet, like faster scan rates, higher line per field ratios are desirable for improved viewing. Recent developments in television systems include digital processing within the receiver to convert scan characteristics, such as scan rates and lines per field. Yet, existing digital receivers process data serially, and because of processing throughput limitations of serial systems, the pixel resolution is limited. A need exists for a television receiving system that receives an incoming signal with one set of scan characteristics and generates a picture with different scan characteristics. The processing throughput should not unduly constrain the level of pixel resolution. Another television application of digital processing devices is digital filters. For example, digital comb filtering is used to separae the luminance and chrominance signals from each other. In general, digital filters are expressed as z-transform functions, in which the terms represent weighted time delays. A problem with existing digital filtering techniques is that calculations are performed with serial processing algorithms and devices, sample-by-sample and tap-by-tap. Yet, newer filter applications require more processing power than is available with these techniques. Some approaches to digital filtering have improved processing speed with custom designed circuits, but this approach sacrifices programming flexibility. As a result, system development is slow and unsophisticated. A need exists for a digital filter that not only achieves a fast throughput, but is also easily adapted to different filter algorithms. The invention concerns a method for digital filtering as set out in claim 3 and a respective digital processing system employing a single-instruction multiple-data processor having a plurality of processing elements for receiving data samples in an ordered sequence, and having an arithmetic unit associated with each processing element for performing computations, and having next-neighbor communications between processing elements, a processor control unit for providing timing and control signals to said single-instruction multiple-data processor, and an instruction generator for providing instructions to said single-instruction multiple-data processor including instructions for performing said computations, an input register for serially receiving said ordered sequence of data samples and for transferring all of said data samples in parallel to corresponding processors, an output register for receiving in parallel all of said data samples stored in said corresponding processing elements and serially transferring said data samples in an ordered sequence out of said single-instruction multiple-data processor, and each processing element having a memory associated therewith, for implementing a horizontal digital filter comprising : said single-instruction multiple-data processor being programmed to implement said horizontal digital filter by using said processing elements as taps of a horizontal digital filter function corresponding to said horizontal digital filter, such that data samples are output from said processing elements in said ordered sequence, means for associating taps of said horizontal digital filter function with processing elements of said single-instruction multiple-data processor, wherein the number of taps of said horizontal digital filter function determines the number of neighboring processors used to process each sample of an incoming data signal ; means for word-serially loading said ordered sequence of data samples into said input register ; means for transferring said ordered sequence of data samples from said input register into said corresponding processing elements ; means for using each processing element to process each of said data samples in parallel to realize a first intermediate result in each processing element ; means for communicating each for said intermediate results to a neighbor processing element of each processing element ; means for storing said intermediate results in said memory associated with said neighbor processing element ; means for processing said first intermediate results, using said neighbor processing element to realize at least one additional intermediate result ; means for repeating said processing, communicating and storing steps until all taps of said horizontal digital filter function have been realized ; means for transferring each of said additional intermediate results in parallel from said processing elements to said output register ; and means for word-serially outputting said additional intermediate results from said output register, wherein said ordered sequence is maintained for a filtered version of said input signal in accordance with said horizontal digital filter function. A device described herein is a programmable digital filtering unit. Data samples are loaded to a single instruction, multiple data processor having a number of processing elements, where every sample is received into a corresponding processing element. The processing elements correspond to taps of a filter function. An arithmetic unit associated with each processing element and near-neighbor communications between processing elements are used to perform the computations of the filter function. Processed sample values are output at the corresponding processing elements so that the data remains ordered in a scan line. A technical advantage of the invention is that input, filter calculations, and output are performed as parallel operations, which achieves fast execution times. Also, the processor is programmable, which permits faster development times for the filter algorithms. BRIEF DESCRIPTION OF THE DRAWINGS Figure 1 is a block diagram of a representative single-instruction multiple-data processor. Figure 2 is a block diagram of a processing element of the processor of Figure 1. Figure 3 is a timing diagram of the processor of Figure 1. Figure 4 illustrates near-neighbor communications among processing elements of the processor of Figure 1. Figure 5 is a block diagram of a digital processing unit that includes the processor of Figure 1. Figures 6A - 6C illustrate a vertical filtering process used for scan conversion. Figure 7 illustrates the process of using a single-instruction multiple-data processor to implement a digital filter. Figure 8 illustrates the use of register files of a single-instruction multiple-data processor to provide a line memory rotation. Figure 9 illustraes a television demodulation process using a horizontal digital filter. Figure 10 illustrates the relationship between an incoming signal and processor elements of a single-instruction multiple-data processor used for horizontal digital filering. Figure 11 illustrates a first method of using a single-instruction multiple-data processor to implement a five-tap horizontal filter. Figure 12 illustrates a second method of using a single-instruction multiple-data processor to implement a five-tap horizontal filter. Figure 13 illustrates a method of using a single-instruction multiple-data processor to implement a three-tap horizontal filter. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Related Applications This application is related to United States patent numbers 5,321,510 (TI-13116 D) issued June 14, 1994 and 4,939,575 (TI-13117 C) issued July 30, 1990. These US patent numbers have a corresponding European Patent Application n° 0 318 218, filed November 11, 1988 and published May 24, 1989 (TI-13116 EU), allowed April 23, 1994. This application is also related to US. Patent N° 5,163,120 (TI-13496) issued November 10, 1992. These patents and application are assigned to Applicant's assignee and their contents are hereby incorporated herein by reference. Serial Video Processor Figure 1 illustrates an example of a serial video processor (SVP) 10, which may also be described as a synchronous vector processor (also SVP). The SVP 10 of Figure 1 is the subject of the copending patent applications cited above. Subsequent sections of this application are directed to devices and processes that use SVP 10. However, these devices and processes are not necessarily limited to use with this particular SVP 10, and variations of SVP 10 may be used. The "serial video" aspects of SVP 10 derive from the fact that it is particularly suited for video processing, where discrete packets of incoming data, which have a uniform size, are input and output in a word-serial manner but are processed in parallel. The "synchronous vector" aspects of SVP 10 derive from the fact that it receives and processes data vectors in synchronization with a real time data source. Essentially, SVP 10 operates by using fine-grained parallelism techniques in which many processing elements operate on the data concurrently. SVP 10 is a general purpose, mask-programmable, single instruction multiple data (SIMD), reduced instruction set computing (RISC) device. Consistent with the SIMD characteristic, SVP 10 has a number of processing elements (PE's), which execute the same instruction at the same time. External microinstructions control primitive logic and arithmetic functions for each clock cycle. Referring to Figures 1 and 2, SVP 10 is a one-dimensional array of one-bit PE's 20. Each PE 20 has the following basic components: a data input register (DIR) 11, two independently addressed register files (RO and R1) 12 and 15, a set of working registers (WR's) 13, a one bit arithmetic unit (ALU) 14, and a data output register (DOR) 16. These are described briefly in this section, and reference to the related patents cited above will provide further description, especially with regard to instructions and timing. DIR 11 can be thought of as the "input layer". RO 12 and R1 15, the WR's 13, and the ALU 14 are the "computational layer". DOR 16 is the "output layer". Although each layer may be independently clocked across each layer, all PE's 20 operate in unison, every clock cycle. The input to DIR 11 is word-serial in the sense that words of an incoming packet of data are received into DIR 11 word by word. Similarly, the output from DIR 16 is word-serial. Although input and output are word-serial, processing of each data packet is parallel. Also, because of the "layered" approach to processing, data input, computation, and data output may be concurrent operations, with each being independently clocked. Each PE 20 performs these operations on an entire vector of data at once, and is thus a "pipeline" that enables several operations to be in various stages at once. When a vector instruction is executed, the elements of the vector are fed into the appropriate pipeline one at a time, delayed by the time it takes to complete one stage of the pipeline. Input and output are in synchronization with the data source, such as a video camera, and with the data sink, such as a raster scan display. For purposes of illustration, SVP 10 has N number of PE's 20, where N = 1440. The memory size is 256 bits for each PE 20, with 128 bits each for R0 and R1, DIR 11 is 40 bits wide and DOR 16 is 24 bits wide. These sizes are discretionary, however, and may be changed without changing the substance of the invention. The input and output bit sizes are included in Figures 1 and 2 to illustrate various input/output and device size relationships. However, these bit sizes may be varied according to the application. Using these values, a single SVP 10 can process data packets of 1 to 1440 words by 40 bits. Typically, the packets are equal in size and represent periodically recurring data, such as lines of a television image, where each packet is digitized into N number of data samples, and where each sample, S(i), i = 1...N, is a data word used to generate an output word. In television applications, where SVP 10 has N PE's 20, N also represents the number of data samples per line. Figure 2 illustrates a single PE 20(i) and its associated components, where i = 1...1440. A vertical slice through SVP 10 of Figure 1 yields an individual PE 20 of Figure 2, thus each PE 20(i) and its components are referred to herein as a "column" with respect to the entire array of SVP 10. DIR 11 and DOR 16 are the basic I/O devices of SVP 10. Both DIR 11 and DOR 16 are arrays of sequentially addressed, dual-ported memory cells. As used in this description, "DIR 11" refers to the entire array, and "DIR 11(i)" refers to the column of DIR 11 that receives data sample S(i). Referring to both Figures 1 and 2, the input array size to SVP 10 permitted by DIR 11 is 1440 words x 40 bits. One port of DIR 11 is organized as 1440 words of 40 bits each and permits DIR 11 to be written into from a 40 bit input line in parallel. Thus, this first port of DIR 11 emulates the write port of a 1440-word line memory, which permits word-serial input. The second port of DIR 11 is organized as 40 words of 1440 bits each, where each bit corresponds to a PE 20(i). This second port provides an interface between DIR 11 and PE's 20. It is physically a part of, and is mapped into, the absolute address space of R0 12. This permits the contents of DIR 11 to be addressed for selection to write into memory and is read in parallel. Like DIR 11, DOR 16 is a two port device. In a manner similar to DIR 11, it provides 1-bit access to each ALU 14(i) and 24-bit output from SVP 10. One port of DOR 16 is organized as 1440 words of 24 bits each. This port functionally emulates the read port of a 1440-word line memory and is used for word-serial output. The second port of DOR 16 is organized as 24 words of 1440 bits each, where each bit corresponds to a PE(i). This second port couples to R1 15, and is written to in parallel. The write and read control signals to DIR 11 and from DOR 16 are explained in detail in subsequent sections of this application, but in general, DIR 11 and DOR 16 each have a 1440-bit word selection commutator, which controls loading to and reading from DIR 11 and DOR 16, respectively. Also, DIR 11 and DOR 16 each have an enable and a reset signal. The data inputs to DIR 11 are controlled by the signals Write Enable (WE), Reset Write (RSTW), and Serial Write Clock (SWCK). WE controls both the write function and the address pointer increment function synchronously with SWCK, which is the data sample clock input. When high, RSTW resets the address pointer to the first word in DIR 11 on the next rising edge of SWCK. The control signals for DOR 16 are Read Enable (RE), Reset Read (RSTR), and Serial Read Clock (SRCK), which operate in an analogous manner. R0 12 and R1 15 each have 128 words by 1 bit of read/write memory per PE 20. Different addressing structures cover the RO 12 and R1 15. However, R0 12 and R1 15 share the same control and timing circuitry. R0 12 and R1 15 are comprised of random access memory (RAM) cells. If dynamic RAM cells are used, they must be refreshed, but typical digital television applications perform the refresh by operating in a faster cycle time than the required refresh period. Each R0 12(i) and R1 15(i) is independently addressable, and is capable of 1-bit read-modify-write cycle such that it can be read, the data operated on by ALU 14, and the result written back to it in a single clock cycle. R0 12 and R1 15 read data at the same time, but write separately. The working register (WR) set 13(i) for each PE 20(i) comprises four registers: M, A, B, and C. These registers are the same, except for their data sources and destinations. Each WR 13(i) is associated with an input multiplexer for providing data to the four inputs of each ALU 14(i). The M register is used for division, multiplication, and logical and conditional operations. Registers A, B, and C are addend, minuend, and carry/borrow registers, respectively. ALU 14 is a simple full adder/subtracter and a one-bit multiplier. The inputs to ALU 14 are from the WR's 13. These ALUs carry out whatever instruction is specified by the control unit of SVP 10. A feature of SVP 10 is that each ALU 14 executes instructions from a set of instructions that operate on data directly. A control unit, which feeds an instruction stream to SVP 10 has an additional set of instructions that provide basic execution control. The control unit is further described below in connection with Figure 5. Figure 3 is a timing diagram of a single cycle of SVP 10. A processing clock (PCLK) is one of three clocks of SVP 10, where each clock corresponds to an input, computational, or output layer. Although the clocks are asynchronous to permit concurrent operations of these three layers, the input and output clocks stop to permit data transfers into and out of the computational layer. In Figure 3, one PCLK cycle, N, has a period T. The labeled timing points indicate interlocked edges, where NCGATE and PCGATE are control signals for sense amplifiers (not shown) and YSEL 0/1 indicates a select signal for R0 12 or R1 15. The sense amplifiers amplify and control the BITLINES for R0 12 and R1 transfers. To achieve single-cycle, 1440-bit, parallel computations, data transfers between R0 12, R1 15, and ALU 14 are precisely timed. Each such data transfer is held off by a computation interlock circuit until the end of computation is indicated. This technique achieves a fast memory/processor data transfer rate. Figure 4 illustrates the near neighbor communications among PE's 20. A left/right (L/R) bus 41 provides direct memory and register read/write from each PE 20 to its four nearest neighbor PE's 20, i.e., the two PE's 20 to the left and the two PE's 20 to the right. To accomplish such communication, each PE 20 generates one output, which is fanned out to its four neighbor PE's 20. This output may be from any one of four sources: a logical 0, the contents of the B register of WR 13, or a location from either R0 12 or R1 15. Each PE 20 also receives four signals, one from each of its four nearest neighbors. As will be explained below, many digital signal processing tasks involve the use of filter algorithms to remove unwanted signal artifacts. The L/R communications of Figure 4 are especially useful for multi-tap FIR filters, which can be factored into five or fewer taps. SVP Video Applications As indicated above, SVP 10 is especially useful for digital video processing. Each signal segment that represents a horizontal line of an incoming television signal is digitized as a data "packet" comprised of a data samples. SVP 10 loads, processes, and outputs data for each pixel on a horizontal line in parallel. The architecture of SVP 10 permits data vectors from multiple pixels, multiple lines, or multiple fields to be processed in parallel, and hence SVP 10 is capable of the "three dimensional processing" required for digital television. A particular advantage of using SVP's 10 is that discrete line memories are not required. Line-by-line storage is emulated in the processing of SVP 10, using a software procedure, referred to as "global rotation". This procedure is explained in the above-cited U.S. patent application, Serial No. 421,499 and in connection with Figure 13 below. Figure 5 illustrates a basic processor system 50a having a single SVP 10. Figure 5B, which also illustrates data inputs to SVP 10. In contrast, Figure 5 illustrates the control, address, and instruction inputs to SVP 10, and may be supplemented with the description of the same circuits in the above-cited U.S. patent application, Serial No. 421,499. Referring now to Figure 5, the basic components of processor system 50a are SVP 10, an SVP control unit 51, and an instruction generator 52. The use of one SVP 10 versus more than one SVP 10 is dependent on the complexity of the processing tasks and hence on the execution time. For full-screen real-time video processing, the operations performed on a line of picture data must be executed in a single 1H period, where H represents the period of one horizontal scan line. However, if 1H is not enough time, more than one SVP 10 may be interconnected and processing tasks partitioned among them. Each SVP 10 need not have the exact configuration of Figures 1 and 2. As already stated, the distinguishing characteristics of an SVP 10 is the ability to process a data packet representing a data packet consisting of an entire line of a television picture in parallel, using a processing element for each pixel. An input control unit 54a, may perform more than one type of input control, depending on the types of tasks to be performed. For loading DIR 11, control circuit 10a includes a means for controlling the WE signal, which is triggered to begin at the end of a horizontal blanking period and clocked so that all columns of DIR 11 are loaded during one horizontal scan period. Input control unit 54a also controls what type of data is received into SVP 10. A particular type of input control circuit, especially designed for high data input rate, is described in the next section of this application. An output control unit 54b may be configured using similar techniques. SVP control unit 51 has several components: controller 51a, vertical timing generator 51b, horizontal timing generator 51c, and constant generator 51d. Ideally, each of these devices is programmable and accesses its own program store memory. In Figure 5, each of these components has its own read only memory (ROM). To facilitate development of processing tasks, programs may be developed on a host system (not shown) and downloaded to each ROM, using standard interface techniques. A host interface 53 may be for either parallel or serial data transfers, for example an RS-232C interface. In operation, SVP control unit 51 generates control signals for SVP 10, which are synchronized with the vertical synchronization signal and the horizontal synchronization signal of the incoming television transmission. These control signals include operating constants, instructions, and timing signals. As an overview of the timing operation of SVP control unit 51, controller 51a controls the video signal processing at-a field or frame rate, vertical timing generator 51b controls processing at a line rate, and horizontal timing generator 51c controls processing at a pixel rate. SVP control unit 51 also provides timing and control signals to other system components, such as for horizontal and vertical synchronization. These latter timing signals are "external" in the sense that they do not control processor system 50a. Instead they control devices such as field memories, as described in subsequent sections of this application. Controller 51a receives and interprets external commands from a main television receiver control unit (shown in Figure 5B). It generates a series of control codes to vertical timing generator 51b and horizontal timing generator 51c. Controller 51a is programmable with a variety of instructions, including conditional and vectored jumps. Vertical timing generator 51b provides control codes to horizontal timing generator 51c, constant generator 51d, and instruction generator 52. It provides timing to external circuits requiring a timing resolution of one horizontal line. Horizontal timing generator 51c generates timing signals for circuits requiring timing edges at sample clock rates, such as DIR 11, DOR 16, field memories, and A/D and D/A converters. It is capable of producing timing edges with a resolution as small as one sample clock. Similarly, constant generator 51d provides constant values to individual PE's 20. There are two main reasons for using such constants. First, it is possible to map waveforms onto the PE's 20. Second, local constants distinguish the I chrominance signal from the Q signal, and permit the PE's 20 to multiplex and demultiplex the chrominance signal and to modify algorithms in the horizontal direction when merging two images. Instruction generator 52 receives algorithm specifier codes from vertical timing generator 51b and condition flags from horizontal timing generator 51c. It outputs microinstructions to ALU 14, and addresses for RO 12 and R1 15. Also, instruction generator 52 provides basic execution control instructions, such as for jumps, calls and returns, test flags, and global rotation. Instruction generator 52 is associated with program storage, such as a ROM, to which instructions may be downloaded from a host system (not shown). The various digital television processing tasks performed by processor system 50a may include scan conversion, motion detection, luminance and chrominance signal processing, and interpolation and decimation. Many of these tasks involve the use of filter algorithms to remove unwanted signal artifacts. Special configurations and programming for scan conversion and filtering are explained in subsequent sections of this application. Figures 6A - 6C illustrate a vertical filtering process that accomplishes a 4:3 decimation. The filter is a five-tap filter, and thus uses five data lines. The filter function has 3 sets of coefficients, sets A, B, and C. The coefficient values for each set are a 0 - a 4 , b 0 - b 4 , and c 0 - c 4 , with values determined using digital filter design techniques. In Figure 6A, Lines L' n - L' n-4 are incoming lines, where L' n represents the line that is earliest in time. Lines L n - L n+4 represent the same five data lines from the processing point of view. From this point of view, the earliest incoming line, L' n , is delayed five lines from the current input line, L n . The data lines produce an output line, y n . In Figure 6B, lines L' n - L' n-4 again represent incoming lines but a new input line takes the place of the fifth earlier data line. This is, in effect, a "rotation" in which the five most recent lines are always available for the filter process. For this step, the filter function uses the set B coefficients to produce the next y n . In Figure 6C, the incoming data lines are again rotated so that the five lines most recent in time are available for the filter function. This step produces a third output line, y n , using the set C coefficients. A fourth line would be generated with the same function, but using a fourth set of data lines and the coefficients of set A. Figure 7 illustrates the process of using SVP 10 for vertical filtering. During the first step SVP 10 receives data representing a horizontal line of an incoming television signal. If the scan rate is also being converted, the data is input in accordance with the scan conversion techniques described above. At the same time as the data is input to DIR 11, a processed horizontal line is output from DOR 16. In the second step, the contents of DIR 11 are transferred to R1. In the third step, previously stored lines from R0 12 and the new line from R1 are used for the filter computations, which a performed by ALU 14. For a five-tap filter, the number of previously stored lines used for the computations is four. In the fourth step, the processed line is transferred to DOR 16. The final step uses a global rotation process, in which an individual line memory subset of R0 and R1 may be circularly rotated rather than shifted throughout the memory bank. This global rotation process is one of the advantages of using SVP 10, which eliminates the need for external line memories. Figure 8 illustrates the global rotation process. Five taps from an input signal represent input data samples to a single register file of a PE 20, which may be either R0 12 or R1 15. Each tap is delayed by one horizontal time period, thus the taps represent samples from corresponding sample positions of consecutive lines. Part of the 128 bit memory of R0 12 or R1 15 is allocated as global rotation memory space. For a five-tap filter in which each sample is 8 bits, a 40-bit space is used. This 40-bit space is configured so that each bit of a sample from one line position can be shifted to the corresponding bit positions of the next line's position. The line spaces are labeled as line space A - E. During a global rotation, the first step is to shift each 8-bit sample to the next higher-addressed 8-bit line space. Then, new sample data is written to the first space, i.e., space A. The data that was in space E may be overwritten because it is no longer needed. Finite Impulse Response Filters SVP 10 is useful for other filtering processes, not necessarily limited to television processing. In particular, there are many applications in which horizontal filtering among data samples of a single data packet is desirable. The following description is directed to using a single-instruction multiple-data processor, such as SVP 10, for a horizontal finite impulse response (FIR) filter process. Although for purposes of example, a low pass filter is described, the same techniques may be used to implement any type of horizontal FIR filter. Also, for purposes of illustration, an example of filtering the chrominance signal of a PAL transmission is used. Figure 9 illustrates the basic steps of the separation and demodulation process, including low pass filtering step. Figure 10 illustrates SVP 10 in relation to one line of an input signal, Va. For purposes of example Va has 1024 samples, which are designated as S(i), i = 1...1024. SVP 10 has a corresponding number of PE's 20(i), i = 1...1024. Figure 10 is merely representative of the process and does not purport to explicitly illustrate the various components of the receiving system front end, prior to input into SVP 10. Va is received word-serially into DIR 11. In this example, 1024 samples are loaded to DIR 11 during each 1H period. Transfers of sample values between the register files RO 12 and R1 15 and the operations of ALU achieve the sample delays and computations of the filter function. Data transfers from DIR 11 to memory RO 12 and R1 15 are via ALU 14, such as are explained in the above-cited patent applications, U.S. Serial No. 435,864 and Serial No. 421,499. The general concept of using SVP 10 for horizontal filtering is to correspond filter taps to PE's 20. The terms of the filter function are realized by adding calculated values for each tap to memory in near-neighbor processors to the right. For each output sample, the desired value ends up in the appropriate PE 20. A first method of using SVP 10 for horizontal filtering is illustrated in Figure 16. An example of a desired filter function is: H(z) = (1 + z -1 ) 2 (1 + z -2 ) (1 + z -1 + z -2 ) / 24, where the notation z -n represents a delay of n sample values. Many algorithms exists for calculating coefficient values to obtain a desired filter output response. The quotient, 24, ensures a unity gain and in terms of digital processing, is needed because each term of the function increases the number of bits. It is obtained by multiplying out the filter function, and recognizing that at zero frequency, the sum of the coefficients is 24. Figure 11 is a process diagram, illustrating the computational steps of the filter process. However, Figure 16 represents computations of only a segment of SVP 10, specifically, PE 20(n-2)20(n)...20(n+2), where (n-2), (n) and (n+1) identify PE's 20 that receive samples of line x having a corresponding sample number. The entire parallel computation for filtering an input sample, S(n), from line X to result in the output sample, S(n)'. At the beginning of the computation for line X, S(1) through S(1024) are transferred in parallel from DIR 11 to the corresponding R1 12 for that PE 20. Thus, R1 15(n) of PE(n) contains S(n). The left neighbor PE(n-1) contains the preceding sample, i.e., S(n-1). The right neighbor PE(n+1) contains the next sample, i.e., S(n+1). The computations to produce a single filtered sample value, begin by adding a first sample to its preceding sample. Thus, S(n) is added to S(n-1). The parallelization of the computation requires S(n-1) to be located in PE 20(n-1). The result of the addition is SUM 1(n). The next step is adding SUM 1(n) to SUM1(n-1) to obtain SUM 2(n). Each of the above summing steps involves only a one-processor delay. To obtain the two-processor delay of the next term of the system function, SUM 2(n) is added to SUM 2(n-2) to obtain SUM 3(n). To complete the process, there are two alternate methods. In the first method, SUM 3(n-2) is transferred into RO 12 (n-1) and then added to SUM 3(n-1) in RO to obtain SUM 4(n). Then SUM 4(n) is added to SUM 3(n) to obtain SUM 5(n). In the second method, which is shown in dotted lines in Figure 16, SUM 3(n-2) is added to SUM 3(n-1) to obtain SUM 4(n-1). Then, SUM 4(n-1) is added to SUM 3(n) to obtain SUM 5(n). SUM 5(n) is divided by some predetermined constant. In this example, the constant is 24, derived as explained above. It should be understood that each PE 20 performs the filter function simultaneously. For example, in a five-tap filter function, the PE's 20(n), each process a tap and generate the result of the filter in parallel. Each PE 20(n) overlaps the next PE 20(n+1) by four taps. In other words, the filter's data is taken relative to each PE 20(n). Four of five sample values processed by each PE 20(n) overlap the sample values being processed by its neighbor PE 20(n+1). The filter of Figure 11 requires the filter function to be factored into the above-described form. Yet, not all filter operations can be factored in this manner. The same low pass filter as described above can be realized with the following function: H(z) = (1 + 3z -1 + 5z -2 + 6z -3 + 5z -4 + 3z -5 + z -6 ) / 24. This function was derived by factoring the previously described function into lower order terms. The L and 2L near-neighbor communications, as shown in Figure 4, can be used to realize delays of one and two samples. Figure 12 illustrates the add-multiply calculations for this second five-tap filter: y(n) = x(n) + 3x(n-1) + 5x(n-2) + 6x(n-3) + 5x(n-4) + 3x(n-5) + x(n-6), where x(n)...x(n-6) represent data sample values delayed by 0...6 1H periods. Although only the calculatons for PE's 20(9) and 20(10) are arbitrarily selected and shown, identical computations for all PE's 20(n) are performed simultaneously. The above filter function may be efficiently realized in four stages, with the following four equations: y1(n) = x(n) + x(n-1) y2(n) = x(n) + x(n-1) y3(n) = x(n) + x(n-2) y4(n) = x(n) + x(n-1) + x(n-2). These equations contain delays of no more than two samples. An operand that is delayed by two samples may be accessed via the 2L communication input of each PE 20(n), as shown in Figure 4. For PE 20(10), the first stage is: x10b(n) = x10a(n) + x10a(n-1), and because of the inherent delay due to the data structure, x10a(n-1) is the same as x9a(n). Thus, x10b(n) = x10a(n) + x10b(n). As indicated in Figure 12, a value in R0 12(10) is added to the value stored in R0 12(9) of the left hand neighbor PE 20, and the values are summed into R1 15(10). The second stage is the same as the first stage, so that: x10c(n) = x10b(n) + x9b(n). For this operation, both operands are from R1 15 because it holds the result of the previous operation. The third stage is similar to the second stage except that bits are summed with the accumulator from the 2L neighbor. The equation is: x10d(n) = x10c(n) + x8c(n). This represents the two-sample delay of the third equation of the set of four equations. The fourth stage requires an intermediate sum in R0 12 from operands in the 2L and L neighbors. This is added to the previously accumulated result in R1 15(10). The function implemented in stage four is: x10e(n) = x8d(n) + x9d(n) + x10d(n). This relates directly to the fourth equation. To verify the above operations, the values may be substituted as: y(10) = 7 + 3(6) + 5(5) + 6(4) + 5(3) + 3(2) + 1 = 96, where x(n), x(n-1), ... x(n-6) are the input values of PE 20(4) - PE 20(10). As indicated by Figures 11 and 12, SVP 10 implements a multi-tap filter without the need to impose delays in other parallel signal paths. The center tap of the filter is assumed to be a reference point and is associated with the current data. PE's 20 to the right and left of the center PE 20 are associated with older and newer data respectively. For example, for a five-tap filter, reaching two PE's left and 2 PE's right makes up the five taps. No delay in the horizontal direction is incurred and the output is in phase with the reference input at the center of the filter. Figure 13 illustrates another method of using a single-instruction multiple-data processor, such as SVP 10, to implement a horizontal FIR filter. For purposes of simplifying the explanation, an example having only three coefficients is assumed: H(z) = 1 + 3z -1 + z -2 . This is a three-tap filter, and as indicated in Figure 18, requires only a one-processor delay in each step. Thus, this method is referred to herein as the "one-processor delay method" as opposed to the "two-processor delay methods" of Figures 16 and 17. As in the two-processor delay methods, SVP 10 is loaded with a line of sample values, S(1)...S(1024), with the 1024 length sample being used as an example only. Figure 18 shows the calculations only with respect to three PE's 20, i.e., PE 20(n-2), PE 20(n-1), and PE 20(n). The registers R0 12 and R1 15 are used as accumulators to hold temporary results. First, S(n-2) and S(n-1) are added to obtain SUM 1(n-1). Then, this sum is added to twice the value of S(n-1). The result is SUM 2(n-1). Finally, SUM 2(n-1) is added to S(n) to obtain SUM 3(n). As desired, SUM 3(n) ends up in the accumulator of PE 20(n). The same process can be easily extended to other filters, requiring fewer or more taps. For real-time applications, the primary limitation as to length is processing time. For example, to achieve real-time television processing, the algorithm should take no longer than the horizontal period for a line, i.e., 1H. A particular advantage of the filter described herein is that processing unit 50a may be used so that programs can be developed on a host system and downloaded to control unit 51 and instruction generator 52. Other Embodiments Although the invention has been described with reference to specific embodiments, this description is not meant to be construed in a limiting sense. Various modifications of the disclosed embodiments, as well as alternative embodiments of the invention will be apparent to persons skilled in the art.

Claims: A digital processing system employing a single-instruction multiple-data processor (10) having a plurality of processing elements (20) for receiving data samples in an ordered sequence, and having an arithmetic unit (14) associated with each processing element for performing computations, and having next-neighbor communications (L, L2, R, R2) between processing elements, a processor control unit (51) for providing timing and control signals-to said single-instruction multiple-data processor (10), and an instruction generator (52) for providing instructions to said single-instruction multiple-data processor (10) including instructions for performing said computations, an input register (11) for serially receiving said ordered sequence of data samples and for transferring all of said data samples in parallel to corresponding processors, an output register (16) for receiving in parallel all of said data samples stored in said corresponding processing elements and serially transferring said data samples in an ordered sequence out of said single-instruction multiple-data processor, and each processing element having a memory associated therewith, the processing system being characterised by implementing a horizontal digital filter comprising : said single-instruction multiple-data processor (10) being programmed to implement said horizontal digital filter by using said processing elements as taps of a horizontal digital filter function corresponding to said horizontal digital filter, such that data samples are output from said processing elements in said ordered sequence, means for associating taps of said horizontal digital filter function with processing elements of said single-instruction multiple-data processor (10), wherein the number of taps of said horizontal digital filter function determines the number of neighboring processors used to process each sample of an incoming data signal ; means for word-serially loading said ordered sequence of data samples into said input register ; means for transferring said ordered sequence of data samples from said input register into said corresponding processing elements ; means for using each processing element to process each of said data samples in parallel to realize a first intermediate result in each processing element ; means for communicating each for said intermediate results to a neighbor processing element of each processing element ; means for storing said intermediate results in said memory associated with said neighbor processing element ; means for processing said first intermediate results, using said neighbor processing element to realize at least one additional intermediate result ; means for repeating said processing, communicating and storing steps until all taps of said horizontal digital filter function have been realized ; means for transferring each of said additional intermediate results in parallel from said processing elements to said output register ; and means for word-serially outputting said additional intermediate results from said output register, wherein said ordered sequence is maintained for a filtered version of said input signal in accordance with said horizontal digital filter function. The digital processing system of claim 1 further comprising an interface for downloading said instructions from a host development system. A method for digital filtering in a single-instruction multiple-data processor (10) having a plurality of processing elements (20) for receiving data samples in an ordered sequence, and having an arithmetic unit (14) associated with each processing element for performing computations, and having next-neighbor communications (L, L2, R, R2) between processing elements, a processor control unit (51) for providing timing and control signals to said single-instruction multiple-data processor (10), and an instruction generator (52) for providing instructions to said single-instruction multiple-data processor (10) including instructions for performing said computations, an input register (11) for serially receiving said ordered sequence of data samples and for transferring all of said data samples in parallel to corresponding processors, an output register (16) for receiving in parallel all of said data samples stored in said corresponding processing elements and serially transferring said data samples in an ordered sequence out of said single-instruction multiple-data processor (10), and each processing element having a memory associated therewith, said method characterised by : associating taps of said horizontal digital filter function with processing elements of said single-instruction multiple-data processor (10), wherein the number of taps of said horizontal digital filter function determines the number of neighboring processors used to process each sample of an incoming data signal ; word-serially loading said ordered sequence of data samples into said input register ; transferring said ordered sequence of data samples from said input register into said corresponding processing elements ; using each processing element to process each of said data samples in parallel to realize a first intermediate result in each processing element ; communicating each of said intermediate results to a neighbor processing element of each processing element ; storing said intermediate results in said memory associated with said neighbor processing element ; processing said first intermediate results, using said neighbor processing element to realize at least one additional intermediate result ; repeating said processing, communicating and storing steps until all taps of said horizontal digital filter function have been realized ; transferring each of said additional intermediate results in parallel from said processing elements to said output register ; and word-serially outputting said additional intermediate results from said output register, wherein said ordered sequence is maintained for a filtered version of said input signal in accordance with said horizontal digital filter function.

Inventors: CHAUVEL GERARD, CHILDERS JIMMIE D, MIYAGUCHI HIROSHI, CHAUVEL, GERARD,, CHILDERS, JIMMIE D., MIYAGUCHI, HIROSHI,, Chauvel, Gérard,
Applicants: TEXAS INSTRUMENTS FRANCE, TEXAS INSTRUMENTS INC, TEXAS INSTRUMENTS INCORPORATED
Application year: 1990
Main classification: G06T1
IPC codes: H04N5, H03H17, G06T1