Name
Abstract | ||
|---|---|---|
The shared memory model helps parallel programming productivity, but it also has a high hardware cost and imposes scalability constraints. Ultimately, higher performance will use distributed memories, which scales better but requires programmers to manually transfer data between local memories, which is a complex task. Distributed memories are also more energy efficient than shared memories, and are used in a family of embedded computing solutions called multi processor system on chip (MPSoC). |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1145/2851141.2851195 | PPOPP |
Keywords | Field | DocType |
memory allocation,global address space,distributed shared memory | Uniform memory access,Shared memory,Computer science,Parallel computing,Distributed memory,Cache-only memory architecture,Data diffusion machine,Memory management,Distributed shared memory,Memory organisation,Distributed computing | Conference |
Volume | Issue | ISSN |
51 | 8 | 0362-1340 |
Citations | PageRank | References |
0 | 0.34 | 3 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| François Gindraud | 1 | 0 | 0.34 |
| Fabrice Rastello | 2 | 482 | 38.30 |
| Albert Cohen | 3 | 85 | 10.03 |
| François Broquedis | 4 | 157 | 11.99 |