Abstract:
Hardware fuzzing has emerged as a promising automatic verification technique to efficiently discover and verify hardware vulnerabilities. However, hardware fuzzing can be...Show MoreMetadata
Abstract:
Hardware fuzzing has emerged as a promising automatic verification technique to efficiently discover and verify hardware vulnerabilities. However, hardware fuzzing can be extremely time-consuming due to compute-intensive iterative simulations. While recent research has explored several approaches to accelerate hardware fuzzing, nearly all of them are limited to single-input fuzzing using one thread of a CPU-based simulator. As a result, we propose Gen-Fuzz, a GPU-accelerated hardware fuzzer using a genetic algorithm with multiple inputs. Measuring experimental results on a real industrial design, we show that GenFuzz running on a single A6000 GPU and eight CPU cores achieves 80× runtime speed-up when compared to state-of-the-art hardware fuzzers.
Published in: 2023 60th ACM/IEEE Design Automation Conference (DAC)
Date of Conference: 09-13 July 2023
Date Added to IEEE Xplore: 15 September 2023
ISBN Information: