Name
Abstract | ||
|---|---|---|
This is a massively parallel ATPG that explores device-level, block-level and word-level parallelism in GPU. Eight-detect transition fault ATPG experiments on large benchmark circuits show that our technique achieved 5.6 and 1.6 times speedup compared with a single-core and 8-core CPU commercial tool, respectively. Test patterns selected from our test set are about the same length and quality as those selected from commercial N-detect ATPG. To the best of our knowledge, this is the first proposed GPU-based ATPG algorithm. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1145/2463209.2488769 | DAC |
Keywords | DocType | ISSN |
gpu-based n-detect transition fault,proposed gpu-based atpg algorithm,benchmark circuits,commercial n-detect atpg,gpu,word level parallelism,times speedup,test pattern,test set,gpu based n-detect transition fault atpg,8-core cpu commercial tool,parallel atpg,graphics processing units,large benchmark circuit,test patterns,multiprocessing systems,block level parallelism,device level parallelism,word-level parallelism,test generation,n-detect,parallel,eight-detect transition fault atpg | Conference | 0738-100X |
Citations | PageRank | References |
6 | 0.64 | 13 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kuan-Yu Liao | 1 | 23 | 2.89 |
| Sheng-Chang Hsu | 2 | 11 | 1.10 |
| James Chien-Mo Li | 3 | 187 | 27.16 |