Abstract:
A microelectronic device design verification system and method estimates the entropy of stimuli communicated over an interface to verify a microelectronic device design and feeds back the estimated entropy to alter the generation of stimuli to improve the design state space verified by additional stimuli applied to the microelectronic device design. For instance, predetermined factors used for random or directed generation of stimuli are altered based on the estimated entropy of stimuli communicated over an interface to a microelectronic device design software model or hardware integrated circuit implementation. The predetermined factors are adjusted so that subsequent stimuli has a desired impact on the estimated entropy, such as an increase in entropy that indicates a more complete microelectronic device design verification.

Description:
BACKGROUND OF THE INVENTION  
         [0001]    1. Field of the Invention  
           [0002]    The present invention relates in general to the field of microelectronic device verification, and more specifically to a method and system for entropy driven verification of a microelectronic device design.  
           [0003]    2. Description of the Related Art  
           [0004]    Microelectronic device designs typically undergo a rigorous verification process before general commercial release. Initial high-level designs specify circuits to perform designed functions, such as generating a predetermined output for a given input. Automated tools then generally take the high-level designs to create a low-level design, such as with gates and transistors fabricated in a semiconductor material. Upon completion of the low-level design, the microelectronic device design is then typically verified with computer simulations and with hardware implementations of the microelectronic device design as an integrated circuit. In the computer simulation environment, predetermined stimulus is applied to a computer model of the low-level design and the simulated output generated by the stimulus is examined to determine that the microelectronic device design performs the designed function, such as by outputting an expected response to the stimulus. In a hardware verification, electrical signal stimuli are input into an integrated circuit having the microelectronic device design and the output response is compared with an expected response to verify that the integrated circuit operates as designed.  
           [0005]    Verification of microelectronic device designs is often a complex and time-consuming process. Integrated circuits have grown increasingly complex and typically have millions of transistors that perform a myriad of functions. Complete design specification and complete verification are often not practical, particularly with complex integrated circuits and tight commercial release dates. Instead, verification generally relies on directed stimuli generated to verify selected functions and random stimuli over a limited duration generated to verify as much of the design state space as practical. Random generation typically uses weights that affect the values of randomly generated stimuli and allows some directed coverage of desired design state space. A combination of directed and random verification testing along with the design state space covered by the verification testing allows an estimation of the stability of the microelectronic device design. Stability determinations generally grow more accurate as the time for application of random stimuli increases; however, even extensive random verification cannot guarantee the status of a microelectronic device design.  
         SUMMARY OF THE INVENTION  
         [0006]    In accordance with the present invention, a method and system are provided for entropy driven verification of a microelectronic device design that accelerates the verification process to achieve a more complete coverage of a design state space in a reduced time. A feedback loop estimates the status of explored areas in a design state space and adjusts stimuli generation to converge on uncovered areas. More specifically, an entropy estimator estimates the entropy of a communication interface that communicates stimuli and responses between a simulation engine and a test engine. An entropy feedback engine uses the estimated entropy to adjust the stimuli output by simulation engine to have a desired effect on the estimated entropy. The estimated entropy provides a measure of design state space coverage by estimating the probability mix of instructions for the stimuli communicated over the interface to the test engine. The entropy feedback engine converges verification coverage to unexplored areas of the design state space by adjusting predetermined factors of random generation or direct stimuli engines so that subsequent stimulus from these stimuli engines increases entropy, thus resulting in a greater probability mix of instructions represented by the stimuli communicated over the communication interface. By adjusting stimuli to have a desired effect on estimated entropy, the feedback loop accelerates verification coverage and provides a more complete verification for a given time period. 
       
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS  
       [0007]    The present invention may be better understood, and its numerous objects, features and advantages made apparent to those skilled in the art by referencing the accompanying drawings. The use of the same reference number throughout the several figures designates a like or similar element.  
         [0008]    [0008]FIG. 1 depicts a block diagram of a system for adjusting stimuli generation based on estimated interface entropy; and  
         [0009]    [0009]FIG. 2 depicts a flow diagram of a process for adjusting stimuli generation based on estimated interface entropy. 
     
    
     DETAILED DESCRIPTION  
       [0010]    Microelectronic device design verification attempts to identify errors by applying stimuli to a simulation or integrated circuit embodying the design and comparing the response of the simulation or integrated circuit with an expected response. Specific design state spaces are covered with directed verification that seeks to apply stimuli that uses selected functions of the microelectronic device design. Other design state spaces are covered with random verification that seeks to apply randomly generated stimuli to other functions of the microelectronic device design. The stability of the microelectronic device design is estimated from the detected errors and the verification coverage. With more complex microelectronic device designs, large numbers of randomly generated stimuli are generally applied in order to obtain an estimate of stability having reasonable reliability, however, verification with large numbers of randomly generated stimuli is a time consuming process. The present invention accelerates the verification process by estimating in real time the coverage of stimuli for the microelectronic device design state space and adjusting the generation of stimuli to cover unexplored design state space.  
         [0011]    Microelectronic devices accept stimuli through input interfaces and output results for the stimuli through output interfaces. Typically, input and output interfaces are physical wires that transmit electronic signals to and from a microelectronic device or that transmit signals within blocks, such as FSMs. The present invention models input or output interfaces as communication channels and evaluates the coverage of stimuli or results from stimuli by evaluating the interface entropy as a communication channel. Entropy of an interface is estimated at an arbitrary starting point based on an initial simulation and then entropy randomization from the initial simulation is adjusted with observed entropy estimations, either with random adjustments, previously recorded simulation runs, predetermined algorithms or new arbitrary starting conditions.  
         [0012]    In one embodiment, design state space covered by stimuli is measured by estimating the entropy of a communication interface that provides the stimuli to a test engine, and convergence on uncovered design state space is accomplished by adjusting random generation weights so subsequent randomly-generated stimuli increases the entropy of the communication interface. The concept of entropy in communication theory is a measurement of the average information or uncertainty associated with an interface. For a source output a j  that occurs with probability p(a j ), the average amount of information per symbol selection or entropy H(p) is stated by the equation:  
         H        (   p   )       =     -       ∑     j   =   0       J   -   1              p        (     a   j     )                     log                 2                   p        (     a   j     )                     bits        /        symbol                               
 
         [0013]    Estimated entropy for a communication interface between a stimuli source and a test engine provides a measure of the probability mix of instructions of the stimuli to the microelectronic device design. In order to provide accelerated design state space coverage, a feedback loop uses estimated entropy of the communication interface to adjust stimuli generation. For instance, random generation weights are adjusted to provide stimuli that increases the communication interface estimated entropy, thus providing an increased probability mix of instructions applied to the microelectronic device design.  
         [0014]    Referring now to FIG. 1, a block diagram depicts a verification system  10  for adjusting stimuli generation based on estimated entropy to adjust verification design state space coverage for a microelectronic device design. A simulation module  12  generates stimuli for application to a microelectronic device design and compares the actual response of the microelectronic device design to the stimuli against an expected response to detect errors. Test stimuli and responses are communicated between simulation module  12  and a test module  14  over a communication interface  16 . Test module  14  includes hardware or software embodiments of the microelectronic device design to test the response of the hardware or software design to the stimuli. For instance, a design model simulation engine  18  applies stimuli to a software model of the microelectronic device design, and a design hardware test board engine  20  applies stimuli to an integrated circuit that embodies the microelectronic device design.  
         [0015]    Simulation module  12  generates stimuli with a stimuli engine  22  and compares the actual and expected response of the microelectronic device design to the stimuli with a results engine  28 . A directed stimuli engine  24  generates directed stimuli for directed testing and a random stimuli engine  26  generates random stimuli for communication to test module  14  through communication interface  16 . Directed testing uses predetermined factors to generate stimuli directed to the testing of specific functions of a microelectronic device design. For instance, directed testing may be used to ensure proper functioning of design specifics that are more commonly subject to failure or that otherwise raise concerns during verification. Random testing uses predetermined factors, such as random generation weights, to generate random stimuli meant to provide random coverage of design state space. For instance, alterations to random generation weights results in changes in design state space coverage of the stimuli randomly generated. Results engine  28  accepts the actual response of the microelectronic device design from test module  14  through communication interface  16  and compares the actual response with an expected response to the applied stimuli. For instance, a correlation matrix  30  correlates actual and expected responses and identifies errors if an actual response differs from an expected response.  
         [0016]    Over time, direct and randomly generated stimuli test microelectronic device design state space to detect errors. However, direct and randomly generated stimuli cannot guarantee complete coverage of design state space or coverage of areas of concern for a given design. In order to measure coverage of stimuli applied to a microelectronic device design, a stimuli feedback loop  32  estimates coverage provided by information communicated over communication interface  16  and adjusts the predetermined factors of directed stimuli engine  24  and random stimuli engine  26  to obtain a desired coverage. For instance, stimuli sent from stimuli engine  22  is observed as it passes through communication interface  16  and the observation is used to estimate design state space coverage provided by the stimuli. The estimate of design state coverage is used to calculate adjustments to predetermined factors, such as random generation weights, to coax coverage of desired design state space. In addition or as an alternative, stimuli feedback loop  32  estimates design state space coverage from responses of the microelectronic device design to the stimuli and adjusts the predetermined factors to coax coverage of desired design state space from a response view. Estimates of coverage of design state space are made based on data or signals across communication interface  16 , such as simulation data associated with testing of design model simulation engine  18  or electrical signals associated with testing of design hardware, such as an integrated circuit that embodies the microelectronic device design.  
         [0017]    Stimuli feedback loop  32  estimates design state space coverage of applied stimuli by analyzing communication interface  16  as a communication channel. Communication channel  16  is analyzed with an entropy function that estimates the average information or uncertainty of communication interface  16  to maximize the number of stimuli bits applied to the microelectronic device design, thus improving coverage. An entropy estimator  34  estimates the entropy of communication interface  32  to provide a quantification of the probability mix of instructions sent as stimuli through communication interface  16 . An entropy feedback engine  36  calculates adjustments to the predetermined factors or directed stimuli engine  24  or random stimuli engine  26  to achieve or maintain a desired entropy, thus providing a desired probability mix of instructions. For instance, entropy feedback engine  36  calculates adjustments to the predetermined factors to attempt to increase or maximize the entropy estimated by entropy estimator  34  in order to increase or maximize the amount of information represented by stimuli communicated over communication interface  16 . In one embodiment, entropy estimator  34  and entropy feedback engine  36  are implemented with one or more neural networks. Stimuli feedback loop  32  may cross correlated entropy estimations with coverage indicated by correlation matrix  30 . The increased probability mix of instructions associated with increased entropy improves design state space coverage in a reduced time. The implementation of a feedback loop to adjust the entropy of communication interface  16  coaxes the generation of stimuli that converges on uncovered design state space.  
         [0018]    Referring now to FIG. 2, a flow diagram depicts a process for adjusting stimuli generation based on an estimated entropy of communication interface  16 . The process begins at step  38  with the generation of stimuli using predetermined factors for application to microelectronic device design implemented with a model simulation or integrated circuit. The generated stimuli may include random and direct stimuli generated with the predetermined factors set to cover a predetermined design state space. At step  40 , the stimuli is applied to the microelectronic device design through communication interface  16  to generate a response. The verification of the microelectronic device design is accomplished by the return of actual responses that are valid for the applied stimuli.  
         [0019]    At step  42 , the stimuli is measured at communication interface  16 , such as by reading data or measuring signals transferred through communication interface  16 . At step  44 , the entropy of communication interface  16  is estimated, such as by applying the read data or measured signals to a neural network. The estimated entropy may include all stimuli communicated across communication interface or stimuli from a selected test period. For instance, the estimated entropy may include directed and random stimuli to estimate the overall probability mix of instructions applied to the microelectronic device or may instead estimate just random stimuli or random stimuli from a defined time period that are associated with selected random generation weights. At step  46 , the predetermined factors associated with the generation of the stimuli are adjusted to provide a desired effect on the entropy of communication interface  16 . For instance, random weights are adjusted to increase entropy, thus resulting in improved coverage of design state space. The process then returns to step  38  for the generation of stimuli with the updated predetermined factors. As the number of iterations increases, the estimated entropy provides a quantification of design state space coverage provided by the stimuli communicated over communication interface  16 .  
         [0020]    Stimuli feedback loop  32  provides a feedback path that improves design state space coverage for random tools by using estimated coverage to alter random generation of stimuli and allows leveraging of existing directed stimuli suites for coverage of desired design state space. The use of real time estimates of entropy to update factors for generation of stimuli accelerates design state coverage by estimating the status of explored areas in design state space and generating stimuli that converges coverage to unexplored areas. In this manner, both model simulation and integrated circuit verification of a microelectronic device design are completed more quickly and with improved diagnostics of errors. Further, regression results of a given microelectronic device design are estimated not just on pass and fail results, but also entropy which quantifies design state space coverage.  
         [0021]    The present invention is well adapted to attain the advantages mentioned as well as others inherent therein. While the present invention has been depicted, described, and is defined by reference to particular embodiments of the invention, such references do not imply a limitation on the invention, and no such limitation is to be inferred. The invention is capable of considerable modification, alteration, and equivalents in form and function, as will occur to those ordinarily skilled in the pertinent arts. The depicted and described embodiments are examples only, and are not exhaustive of the scope of the invention.  
         [0022]    The above-discussed embodiments include software modules that perform certain tasks. The software modules discussed herein may include script, batch, or other executable files. The software modules may be stored on a machine-readable or computer-readable storage medium such as a disk drive. Storage devices used for storing software modules in accordance with an embodiment of the invention may be magnetic floppy disks, hard disks, or optical discs such as CD-ROMs or CD-Rs, for example. A storage device used for storing firmware or hardware modules in accordance with an embodiment of the invention may also include a semiconductor-based memory, which may be permanently, removably or remotely coupled to a microprocessor/memory system. Thus, the modules may be stored within a computer system memory to configure the computer system to perform the functions of the module. Other new and various types of computer-readable storage media may be used to store the modules discussed herein. Additionally, those skilled in the art will recognize that the separation of functionality into modules is for illustrative purposes. Alternative embodiments may merge the functionality of multiple modules into a single module or may impose an alternate decomposition of functionality of modules. For example, a software module for calling sub-modules may be decomposed so that each sub-module performs its function and passes control directly to another sub-module.  
         [0023]    Consequently, the invention is intended to be limited only by the spirit and scope of the appended claims, giving full cognizance to equivalents in all respects.