Name
Abstract | ||
|---|---|---|
The performance of a task running on a many-core with distributed shared last-level cache (LLC) strongly depends on two parameters: the power budget needed to guarantee thermally-safe operation and the LLC latency. The task's thread-to-core mapping determines both the parameters and needs to make a trade-off because both cannot be simultaneously optimal. Arrival and departure of tasks on a many-co... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TC.2020.3023022 | IEEE Transactions on Computers |
Keywords | DocType | Volume |
Task analysis,Instruction sets,Analytical models,Artificial neural networks,Predictive models,Computer architecture,Computational modeling | Journal | 70 |
Issue | ISSN | Citations |
10 | 0018-9340 | 1 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Martin Rapp | 1 | 6 | 4.83 |
| Anuj Pathania | 2 | 181 | 14.97 |
| Tulika Mitra | 3 | 2714 | 135.99 |
| J. Henkel | 4 | 4471 | 366.50 |