Name
Abstract | ||
|---|---|---|
Parallel computing in heterogeneous environments is drawing considerable attention due to the growing number of these kind of systems. Adapting existing code and libraries to such systems is a fundamental problem. The performance of this code is affected by the large interdependence between the code and these parallel architectures. We have developed a dynamic load balancing library that allows parallel code to be adapted to heterogeneous systems for a wide variety of problems. The overhead introduced by our system is minimal and the cost to the programmer negligible. The strategy was applied to a Dynamic Programming Algorithm, the Resource Allocation Problem. This code has been implemented on different heterogeneous architectures, including an heterogeneous cluster, a multicore system, a single GPU, and a multi-GPU system. The unbalance nature of the RAP algorithm shows the success of our load balancing library on such architectures. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/HPCS.2010.5547097 | HPCS |
Keywords | Field | DocType |
gpu,dynamic programming,irregular code,cuda,resource allocation problem,dynamic load balancing,coprocessors,resource allocation,resource management,parallel computer,load balance,dynamic programming algorithm | Load management,Dynamic programming,GPU cluster,Load balancing (computing),CUDA,Computer science,Parallel computing,Resource allocation,Coprocessor,Multi-core processor,Distributed computing | Conference |
ISBN | Citations | PageRank |
978-1-4244-6827-0 | 3 | 0.43 |
References | Authors | |
9 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alejandro Acosta | 1 | 55 | 8.98 |
| Robert Corujo | 2 | 3 | 0.43 |
| Vicente Blanco | 3 | 41 | 5.64 |
| F. Almeida | 4 | 343 | 49.54 |