Strengthening Model Checking Techniques with Inductive Invariants

This paper describes optimized techniques to efficiently compute and reap benefits from inductive invariants within SAT-based model checking. We address sequential circuit verification, and we consider both equivalences and implications between pairs of nodes in the logic networks. First, we present a very efficient dynamic procedure, based on equivalence classes and incremental SAT, specifically oriented to reduce the set of checked invariants. Then, we show how to effectively integrate the computation of inductive invariants within state-of-the-art SAT-based model checking procedures. Experiments (on more than 600 designs) show the robustness of our approach on verification instances on which stand-alone techniques fai

Custom Integrated Circuits

Contains reports on ten research projects.Analog Devices, Inc.IBM CorporationNational Science Foundation/Defense Advanced Research Projects Agency Grant MIP 88-14612Analog Devices Career Development Assistant ProfessorshipU.S. Navy - Office of Naval Research Contract N0014-87-K-0825AT&TDigital Equipment CorporationNational Science Foundation Grant MIP 88-5876

Doctor of Philosophy

dissertationThe embedded system space is characterized by a rapid evolution in the complexity and functionality of applications. In addition, the short time-to-market nature of the business motivates the use of programmable devices capable of meeting the conflicting constraints of low-energy, high-performance, and short design times. The keys to achieving these conflicting constraints are specialization and maximally extracting available application parallelism. General purpose processors are flexible but are either too power hungry or lack the necessary performance. Application-specific integrated circuits (ASICS) efficiently meet the performance and power needs but are inflexible. Programmable domain-specific architectures (DSAs) are an attractive middle ground, but their design requires significant time, resources, and expertise in a variety of specialties, which range from application algorithms to architecture and ultimately, circuit design. This dissertation presents CoGenE, a design framework that automates the design of energy-performance-optimal DSAs for embedded systems. For a given application domain and a user-chosen initial architectural specification, CoGenE consists of a a Compiler to generate execution binary, a simulator Generator to collect performance/energy statistics, and an Explorer that modifies the current architecture to improve energy-performance-area characteristics. The above process repeats automatically until the user-specified constraints are achieved. This removes or alleviates the time needed to understand the application, manually design the DSA, and generate object code for the DSA. Thus, CoGenE is a new design methodology that represents a significant improvement in performance, energy dissipation, design time, and resources. This dissertation employs the face recognition domain to showcase a flexible architectural design methodology that creates "ASIC-like" DSAs. The DSAs are instruction set architecture (ISA)-independent and achieve good energy-performance characteristics by coscheduling the often conflicting constraints of data access, data movement, and computation through a flexible interconnect. This represents a significant increase in programming complexity and code generation time. To address this problem, the CoGenE compiler employs integer linear programming (ILP)-based 'interconnect-aware' scheduling techniques for automatic code generation. The CoGenE explorer employs an iterative technique to search the complete design space and select a set of energy-performance-optimal candidates. When compared to manual designs, results demonstrate that CoGenE produces superior designs for three application domains: face recognition, speech recognition and wireless telephony. While CoGenE is well suited to applications that exhibit a streaming behavior, multithreaded applications like ray tracing present a different but important challenge. To demonstrate its generality, CoGenE is evaluated in designing a novel multicore N-wide SIMD architecture, known as StreamRay, for the ray tracing domain. CoGenE is used to synthesize the SIMD execution cores, the compiler that generates the application binary, and the interconnection subsystem. Further, separating address and data computations in space reduces data movement and contention for resources, thereby significantly improving performance compared to existing ray tracing approaches

CA-BIST for asynchronous circuits: a case study on the RAPPID asynchronous instruction length decoder

Journal ArticleThis paper presents a case study in low-cost noninvasive Built-In Self Test (BIST) for RAPPID, a largescale 120,000-transistor asynchronous version of the Pentium® Pro Instruction Length Decoder, which runs at 3.6 GHz. RAPPID uses a synchronous 0.25 micron CMOS library for static and domino logic, and has no Design-for-Test hooks other than some debug features. We explore the use of Cellular Automata (CA) for on-chip test pattern generation and response evaluation. More specifically, we look for fast ways to tune the CA-BIST to the RAPPID design, rather than using pseudo-random testing. The metric for tuning the CA-BIST pattern generation is based on an abstract hardware description model of the instruction length decoder, which is independent of implementation details, and hence also independent of the asynchronous circuit style. Our CA-BI ST solution uses a novel bootstrap procedure for generating the test patterns, which give complete coverage for this metric, and cover 94% of the testable stuck-at faults for the actual design at switch level. Analysis of the undetected and untestable faults shows that the same fault effects can be expected for a similar clocked circuit. This is encouraging evidence that testability is no excuse to avoid asynchronous design techniques in addition to high-performance synchronous solutions

CA-BIST for asynchronous circuits: a case study on the RAPPID asynchronous instruction length decoder

Journal ArticleThis paper presents a case study in low-cost noninvasive Built-In Self Test (BIST) for RAPPID, a largescale 120,000-transistor asynchronous version of the Pentium® Pro Instruction Length Decoder, which runs at 3.6 GHz. RAPPID uses a synchronous 0.25 micron CMOS library for static and domino logic, and has no Design-for-Test hooks other than some debug features. We explore the use of Cellular Automata (CA) for on-chip test pattern generation and response evaluation. More specifically, we look for fast ways to tune the CA-BIST to the RAPPID design, rather than using pseudo-random testing. The metric for tuning the CA-BIST pattern generation is based on an abstract hardware description model of the instruction length decoder, which is independent of implementation details, and hence also independent of the asynchronous circuit style. Our CA-BI ST solution uses a novel bootstrap procedure for generating the test patterns, which give complete coverage for this metric, and cover 94% of the testable stuck-at faults for the actual design at switch level. Analysis of the undetected and untestable faults shows that the same fault effects can be expected for a similar clocked circuit. This is encouraging evidence that testability is no excuse to avoid asynchronous design techniques in addition to high-performance synchronous solutions