Title :
Artificial Neural Network Simulation on CUDA
Author :
Pendlebury, John ; Xiong, Huanhuan ; Walshe, Ray
Author_Institution :
CloudCore Res. Group, Dublin City Univ., Dublin, Ireland
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.
Keywords :
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; Arrays; Biological neural networks; Computational modeling; Graphics processing units; Neurons; Sensors; CUDA; GPU; Neural-Networks; Simulation;
Conference_Titel :
Distributed Simulation and Real Time Applications (DS-RT), 2012 IEEE/ACM 16th International Symposium on
Conference_Location :
Dublin
Print_ISBN :
978-1-4673-2954-5
DOI :
10.1109/DS-RT.2012.40
