Name
Abstract | ||
|---|---|---|
•Effective utilization of resources in CPU-GPU systems improves the performance and energy efficiency.•Researches focus on collaboratively executing single or multiple tasks on CPU and GPU.•Runtimes for portability of code and task allocation schemes improve the possibility of collaborative execution.•Various research works in the area of cooperative CPU-GPU heterogeneous computing are reviewed and the research gaps are outlined. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.suscom.2018.07.010 | Sustainable Computing: Informatics and Systems |
Keywords | Field | DocType |
Heterogeneous system,CPU-GPU,Multicore CPU,Cooperative execution,Task allocation,Energy saving | Efficient energy use,Massively parallel,Computer science,Parallel computing,Symmetric multiprocessor system,General-purpose computing on graphics processing units,Multi-core processor,Energy consumption,Speedup,Computation | Journal |
Volume | ISSN | Citations |
19 | 2210-5379 | 0 |
PageRank | References | Authors |
0.34 | 55 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Raju K | 1 | 0 | 0.34 |
| Niranjan N. Chiplunkar | 2 | 4 | 2.50 |