Name
Abstract | ||
|---|---|---|
The advent of low cost GPU hardware and user friendly parallel programming APIs, such as NVIDIA CUDA means that affordable, programmable, high-performance computing environments for simulation are now attainable for development of scientific simulations. In this paper the authors present the Mine Hunter program, a parallel simulation of neural networks on NVIDIA CUDA. The simulation consists of 128 mine hunters in a mine field of 8192 mines, running on an Intel Quad Core i5-2500 3.3GHz 2 x Nvidia GeForce GTX 480. The results presented demonstrate that CUDA improves performance by up to 80% compared with the equivalent CPU implementation. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/DS-RT.2012.40 | DS-RT |
Keywords | Field | DocType |
neural nets,parallel architectures,ANN,API,CPU implementation,Intel QuadCore i5-2500,MineHunter program,NVIDIA CUDA,Nvidia GeForce GTX 480,artificial neural network simulation,compute unified device architecture,frequency 3.3 GHz,high-performance computing environments,low cost GPU hardware,parallel simulation,scientific simulations,user friendly parallel programming,CUDA,GPU,Neural-Networks,Simulation | Computer architecture,Parallel simulation,Computer science,CUDA,Parallel computing,General-purpose computing on graphics processing units,User Friendly,Artificial neural network,Multi-core processor | Conference |
ISSN | Citations | PageRank |
1550-6525 | 0 | 0.34 |
References | Authors | |
10 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| John Pendlebury | 1 | 0 | 0.68 |
| Huanhuan Xiong | 2 | 52 | 7.07 |
| Ray Walshe | 3 | 59 | 8.98 |