The performance is shown in the table below.
Datasets | Vertex | Edges | CPU time | FPGA time | Speedup |
coPapersCiteseer | 434102 | 16036720 | 0.26 | 0.309 | 84.14% |
coPapersDBLP | 540486 | 15245729 | 0.31 | 0.317 | 97.79% |
hollywood | 1139905 | 57515616 | 1.78 | 1.21 | 147.11% |
as-Skitter | 1694616 | 11094209 | 0.74 | 0.344 | 215.12% |
cit-Patents | 3774768 | 16518948 | 2.07 | 0.584 | 354.45% |
Note
- Maximal independent set CPU time benchmarking is running on Intel(R) Xeon(R) CPU E5-2667 v3 @ 3.20GHz, cache(2048 KB), cores(31)
- time unit: ms.
- This mis implementation focus on single-kernel-level design and focusing on mid-scale dataset processing. As showed in table, with the increasing of the graph vertex number, the FPGA show increasingly advantage over CPU offloading.
- The performance is tested under config of “set_property -dict [list CONFIG.ECC_EN {false} CONFIG.ECC_SCRUB_EN {false}] [get_bd_cells hmss_0]”