Applying Constrained-Random Verification to Microprocessors
By Jason C. Chen, Synopsys Inc.
December 10, 2007 -- edadesignline.com
Constrained-random verification (CRV) offers a highly effective way to deal with the challenges of microprocessor verification. These verification challenges are overwhelming for many reasons: complex instruction sets, multiple pipeline stages, in-order or out-of-order execution strategies, instruction parallelism, fixed- and floating-point scalar/vector operations, and other features that create a seemly never-ending list of corner cases to exercise. The time required to create traditional directed tests has become unreasonable.
Language features such as the SystemVerilog random sequence generator allow you to create instruction sequences randomly to improve stimulus quality based on a structured set of rules and scenarios. Such random-sequence generation schemes are procedural, however, and do not take full advantage of object-based randomization using constraints.
This article proposes an object-oriented solution for processor verification challenges. The solution covers both a top-down stimulus planning process and a bottom-up implementation solution using SystemVerilog and commercially available base classes (such as those in Synopsys's Verification Methodology Manual, VMM). The description that follows covers the most important parts of this solution and uses a processor supporting the MIPS-I instruction set as an example design under test (DUT).
December 10, 2007 -- edadesignline.com
Constrained-random verification (CRV) offers a highly effective way to deal with the challenges of microprocessor verification. These verification challenges are overwhelming for many reasons: complex instruction sets, multiple pipeline stages, in-order or out-of-order execution strategies, instruction parallelism, fixed- and floating-point scalar/vector operations, and other features that create a seemly never-ending list of corner cases to exercise. The time required to create traditional directed tests has become unreasonable.
Language features such as the SystemVerilog random sequence generator allow you to create instruction sequences randomly to improve stimulus quality based on a structured set of rules and scenarios. Such random-sequence generation schemes are procedural, however, and do not take full advantage of object-based randomization using constraints.
This article proposes an object-oriented solution for processor verification challenges. The solution covers both a top-down stimulus planning process and a bottom-up implementation solution using SystemVerilog and commercially available base classes (such as those in Synopsys's Verification Methodology Manual, VMM). The description that follows covers the most important parts of this solution and uses a processor supporting the MIPS-I instruction set as an example design under test (DUT).
To read the full article, click here
Related Semiconductor IP
- Verification IP for C-PHY
- Band-Gap Voltage Reference with dual 2µA Current Source - X-FAB XT018
- 250nA-88μA Current Reference - X-FAB XT018-0.18μm BCD-on-SOI CMOS
- UCIe D2D Adapter & PHY Integrated IP
- Low Dropout (LDO) Regulator
Related Articles
- A Comparison of Assertion Based Formal Verification with Coverage driven Constrained Random Simulation, Experience on a Legacy IP
- Methodology Independent Exhaustive Constraint Solver for Random Verification and Regression Generation
- Strategies for verifying microprocessors
- Lockdown! Random Numbers Secure Network SoC Designs
Latest Articles
- SCENIC: Stream Computation-Enhanced SmartNIC
- Agentic AI-based Coverage Closure for Formal Verification
- Microarchitectural Co-Optimization for Sustained Throughput of RISC-V Multi-Lane Chaining Vector Processors
- RISC-V Functional Safety for Autonomous Automotive Systems: An Analytical Framework and Research Roadmap for ML-Assisted Certification
- Emulation-based System-on-Chip Security Verification: Challenges and Opportunities