Name
Abstract | ||
|---|---|---|
Heterogeneous multiprocessor system-on-chips (SoCs) provide a wide range of parameters that can be managed dynamically. For example, one can control the type (big/little), number and frequency of active cores in state-of-the-art mobile processors at runtime. These runtime choices lead to more than 10× range in execution time, 5× range in power consumption, and 50× range in performance per watt. Th... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/LCA.2019.2892151 | IEEE Computer Architecture Letters |
Keywords | Field | DocType |
Frequency control,Runtime,Training,Power system management,Power demand,Memory management,Instruments | Power management,Computer science,Parallel computing,Mobile processor,Oracle,Q-learning,Multiprocessing,Memory management,Performance per watt,Distributed computing,Reinforcement learning | Journal |
Volume | Issue | ISSN |
18 | 1 | 1556-6056 |
Citations | PageRank | References |
5 | 0.42 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ujjwal Das Gupta | 1 | 37 | 6.59 |
| Sumit K. Mandal | 2 | 12 | 1.92 |
| Manqing Mao | 3 | 6 | 1.12 |
| Chaitali Chakrabarti | 4 | 1978 | 184.17 |
| Ümit Y. Ogras | 5 | 203 | 15.03 |