Name
Abstract | ||
|---|---|---|
Nowadays, a large number of accelerators are proposed to increase the performance of AI applications, making it a big challenge to enhance existing AI programming frameworks to support these new accelerators. In this paper, we select TensorFlow to demonstrate how to port the AI programming framework to new hardwares, i.e., FPGA and Sunway TaihuLight here. FPGA and Sunway TaihuLight represent two distinct and significant hardware architectures for considering the retargeting process. We introduce our retargeting processes and experiences for these two platforms, from the source codes to the compilation processes. We compare the two retargeting approaches and demonstrate some preliminary experimental results. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/978-3-030-05677-3_4 | NPC |
Field | DocType | Citations |
Computer architecture,Computer science,Source code,Field-programmable gate array,Retargeting,Sunway TaihuLight,Software framework,Distributed computing,Applications of artificial intelligence | Conference | 0 |
PageRank | References | Authors |
0.34 | 16 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jiacheng Zhao | 1 | 28 | 2.71 |
| Yisong Chang | 2 | 5 | 3.92 |
| Denghui Li | 3 | 0 | 1.01 |
| Chunwei Xia | 4 | 0 | 0.34 |
| Huimin Cui | 5 | 119 | 11.40 |
| Ke Zhang | 6 | 75 | 21.74 |
| Xiaobing Feng | 7 | 906 | 112.55 |