Name
Abstract | ||
|---|---|---|
The increasing demand tor more computational power from scientific computing, big data processing, and machine learning is pushing the development of HPC (high-performance computing) systems. As the basic HPC building blocks, modularized server racks with a large number of multicore nodes are facing performance and energy efficiency challenges. This paper proposes RSON, an optical network for rack-scale computing systems. RSON connects processor cores, caches, local memories, and remote memories through a novel inter/intra-chip silicon photonic network architecture. We develop a low-latency scalable channel partition and low-power dynamic path priority control scheme for RSON. Experimental results show that RSON can help rack-scale computing systems achieve up to 6.8X higher performance under the same energy consumption than state-of-the-art systems under the latest APEX (application performance at extreme scale) benchmarks. |
Year | Venue | Field |
|---|---|---|
2018 | PROCEEDINGS OF THE 2018 DESIGN, AUTOMATION & TEST IN EUROPE CONFERENCE & EXHIBITION (DATE) | Computer architecture,Transceiver,Efficient energy use,Computer science,Parallel computing,Communication channel,Network architecture,Chip,Multi-core processor,Energy consumption,Scalability |
DocType | ISSN | Citations |
Conference | 1530-1591 | 0 |
PageRank | References | Authors |
0.34 | 0 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Peng Yang | 1 | 64 | 10.97 |
| Zhengbin Pang | 2 | 49 | 11.18 |
| Zhifei Wang | 3 | 27 | 7.86 |
| Zhehui Wang | 4 | 262 | 24.56 |
| Min Xie | 5 | 20 | 7.20 |
| Xuanqi Chen | 6 | 6 | 5.31 |
| Luan H. K. Duong | 7 | 64 | 9.36 |
| Jiang Xu | 8 | 704 | 61.98 |