Name
Abstract | ||
|---|---|---|
We aim at mapping streaming applications that can be modeled by a series-parallel graph onto a 2-dimensional tiled chip multiprocessor (CMP) architecture. The objective of the mapping is to minimize the energy consumption, using dynamic voltage and frequency scaling (DVFS) techniques, while maintaining a given level of performance, reflected by the rate of processing the data streams. This mapping problem turns out to be NP-hard, and several heuristics are proposed. We assess their performance through comprehensive simulations using the StreamIt workflow suite and randomly generated series-parallel graphs, and various CMP grid sizes. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1142/S0129626413400033 | PARALLEL PROCESSING LETTERS |
Keywords | Field | DocType |
Multicore, energy, period, optimization, DVFS, streaming applications | Data stream mining,Computer science,Parallel computing,Multiprocessing,Heuristics,Frequency scaling,Multi-core processor,Workflow,Energy consumption,Grid,Distributed computing | Journal |
Volume | Issue | ISSN |
23 | 2 | 0129-6264 |
Citations | PageRank | References |
2 | 0.37 | 5 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Anne Benoit | 1 | 342 | 33.74 |
| Rami G. Melhem | 2 | 240 | 16.11 |
| Paul Renaud-Goud | 3 | 35 | 6.57 |
| Yves Robert | 4 | 842 | 70.03 |