GPU-based ATPG System by Scaling Memory Usage and Reducing Data Transfer

Test generation and fault simulation are essential in VLSI automatic test pattern generation (ATPG). Parallel computing on GPU gives another way to improve work performance. Thousands of concurrent threads can be launched simultaneously within GPU. Due to severe GPU memory limitation, scalability algorithm and efficient data transfer are necessary for test generation and fault simulation. In this paper, we present a GPU-based ATPG system that can scale memory usage and reduce data transfer between processors. We utilize several parallelism methods to enhance the system ability. Comparing to a commercial tool run with CPU in single, two, four, and eight cores, experiments show that our algorithm has 3.99, 2.18, 1.17 and 0.94 times of speedup and 0.85, 0.78, 0.76 and 0.73 times of less memory usage, respectively.