Name
Abstract | ||
|---|---|---|
There has been an overwhelming trend in recent years to move towards parallel computing. Hardware manufacturers are increasing the amount of parallelism on a single chip in several ways, including adding more processing cores and accelerators to execute the same instructions on many data items simultaneously. At the other end of the spectrum, as commodity hardware prices fall, it is becoming increasingly affordable to build large-scale, multi-node distributed machines. Similarly, as processor speeds begin to stagnate, software developers will be forced to exploit the parallelism in their applications in order to continue to improve the performance. |
Year | Venue | Keywords |
|---|---|---|
2009 | Proceedings of the 2011 Conference of the Center for Advanced Studies on Collaborative Research | data item,heterogeneous parallel computing system,processing core,parallel application,overwhelming trend,commodity hardware price,hardware manufacturer,parallel computing,processor speed,large parallel machine,software developer,parallel software,large parallel application,parallel system,single chip,heterogeneous system,new parallel programming model,recent year,software development,parallel computer,chip,spectrum |
Field | DocType | Citations |
Task parallelism,Computer science,Parallel computing,Chip,Real-time computing,Exploit,Software,Data parallelism,Commodity hardware,Operating system,Distributed computing | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kit Barton | 1 | 4 | 3.80 |
| Guansong Zhang | 2 | 246 | 23.32 |
| Priya Unnikrishnan | 3 | 200 | 14.67 |