Name
Abstract | ||
|---|---|---|
GPUs have been increasingly used to accelerate graph processing for complicated computational problems regarding graph theory. Many parallel graph algorithms adopt the asynchronous computing model to accelerate the iterative convergence. Unfortunately, the consistent asynchronous computing requires locking or atomic operations, leading to significant penalties/overheads when implemented on GPUs. A... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TKDE.2017.2745562 | IEEE Transactions on Knowledge and Data Engineering |
Keywords | Field | DocType |
Graphics processing units,Image color analysis,Computational modeling,Parallel processing,Kernel,Data transfer,Acceleration | Graph theory,Asynchronous communication,Computational problem,Sequential consistency,Degree of parallelism,Computer science,Theoretical computer science,General-purpose computing on graphics processing units,Artificial intelligence,Machine learning,Graph coloring,Dense graph | Journal |
Volume | Issue | ISSN |
30 | 1 | 1041-4347 |
Citations | PageRank | References |
7 | 0.46 | 29 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xuanhua Shi | 1 | 571 | 57.87 |
| Xuan Luo | 2 | 30 | 10.84 |
| Junling Liang | 3 | 18 | 1.26 |
| zhao peng | 4 | 36 | 15.85 |
| Sheng Di | 5 | 737 | 55.88 |
| Bingsheng He | 6 | 2810 | 179.09 |
| Hai Jin | 7 | 6544 | 644.63 |