Name
Abstract | ||
|---|---|---|
Spectral calculation and analysis have very important practical applications in astrophysics. The main portion of spectral calculation is to solve a large number of one-dimensional numerical integrations at each point of a large three-dimensional parameter space. However, existing widely used solutions still remain in process-level parallelism, which is not competent to tackle numerous compute-intensive small integral tasks. This paper presented a GPU-optimized approach to accelerate the numerical integration in massive spectral calculation. We also proposed a load balance strategy on hybrid multiple CPUs and GPUs architecture via share memory to maximize performance. The approach was prototyped and tested on the Astrophysical Plasma Emission Code (APEC), a commonly used spectral toolset. Comparing with the original serial version and the 24 CPU cores (2.5GHz) parallel version, our implementation on 3 Tesla C2075 GPUs achieves a speed-up of up to 300 and 22 respectively. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/ICPP.2015.13 | ICPP |
Keywords | Field | DocType |
numerical integration, load balancing, GPU, hybrid architecture, spectral calculation | Computer science,Load balancing (computing),Parallel computing,Numerical integration,Astrophysical plasma,Computational science,Parameter space,Multi-core processor | Conference |
ISSN | Citations | PageRank |
0190-3918 | 0 | 0.34 |
References | Authors | |
12 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jian Xiao | 1 | 24 | 9.12 |
| Xingyu Xu | 2 | 3 | 2.41 |
| Ce Yu | 3 | 75 | 15.15 |
| Zhang Jiawan | 4 | 369 | 46.66 |
| Shuinai Zhang | 5 | 0 | 0.34 |
| Li Ji | 6 | 1 | 1.04 |
| Sun Jizhou | 7 | 253 | 47.07 |