Name
Abstract | ||
|---|---|---|
Training Deep Neural Networks (DNNs) models is a time-consuming process that requires immense amount of data and computation. To this end, GPUs are widely adopted to accelerate the training process. However, the delivered training performance rarely scales with the increase in the number of GPUs. The major reason behind this is the large amount of data movement that prevents the system from provid... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ICCAD51958.2021.9643503 | 2021 IEEE/ACM International Conference On Computer Aided Design (ICCAD) |
Keywords | DocType | ISSN |
Training,Deep learning,Design automation,Computational modeling,Scalability,Graphics processing units,Parallel processing | Conference | 1933-7760 |
ISBN | Citations | PageRank |
978-1-6654-4507-8 | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Weizheng Xu | 1 | 1 | 1.02 |
| Ashutosh Pattnaik | 2 | 113 | 4.70 |
| Geng Yuan | 3 | 9 | 3.80 |
| Yanzhi Wang | 4 | 1082 | 136.11 |
| Youtao Zhang | 5 | 1977 | 122.84 |
| Xulong Tang | 6 | 5 | 4.79 |