Name
Abstract | ||
|---|---|---|
Nowadays, Graphics Processing Unit (GPU), as a kind of massive parallel processor, has been widely used in general purposed computing tasks. Although there have been mature development tools, it is not a trivial task for programmers to write GPU programs. Based on this consideration, we propose a novel parallel computing architecture. The architecture includes a parallel programming model, named Gemma, and a programming framework, named April. Gemma is based on generalized matrix operations, and helps to alleviate the difficulty of describing parallel algorithms. April is a high-level framework that can compile and execute tasks described in Gemma with OpenCL. In particular, April can automatically 1) choose the best parallel algorithm and mapping scheme, and generate OpenCL kernels, 2) schedule Gemma tasks based on execution costs such as data storing and transferring. Our experimental results show that with competitive performance, April considerably reduces the programs' code length compared with OpenCL. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/DATE.2011.5763119 | DATE |
Keywords | Field | DocType |
graphics processing unit,programming languages,open computing language,computer graphic equipment,parallel programming,gemma,data storing,opencl kernels,data transferring,parallel computing architecture,parallel algorithms,coprocessors,april,matrix-like parallel programming architecture,sparse matrices,computer architecture,computational modeling,kernel,computer model | Programming language,Parallel algorithm,Computer science,Parallel computing,Compiler,Parallel programming model,Coprocessor,Graphics processing unit,Matrix multiplication,Sparse matrix,Software framework | Conference |
Volume | Issue | ISSN |
null | null | 1530-1591 |
ISBN | Citations | PageRank |
978-1-61284-208-0 | 0 | 0.34 |
References | Authors | |
3 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tianji Wu | 1 | 41 | 3.57 |
| Di Wu | 2 | 0 | 0.34 |
| Yu Wang | 3 | 2279 | 211.60 |
| Xiaorui Zhang | 4 | 144 | 17.71 |
| Hong Luo | 5 | 133 | 8.99 |
| Ning-Yi Xu | 6 | 563 | 36.18 |
| Huazhong Yang | 7 | 2239 | 214.90 |