Title :
Scalable multi-precision simulation of spiking neural networks on GPU with OpenCL
Author :
Yudanov, Dmitri ; Reznik, Leon
Author_Institution :
Adv. Micro Devices (AMD), Austin, TX, USA
Abstract :
Biologically-realistic multi-precision spiking neural network (SNN) simulation is designed and implemented on a new GPU device Radeon™ HD 7970 using OpenCL framework. The implementation aims to investigate the role of time precision in simulated SNNs. Simulation methods and GPU platforms are reviewed. Simulation model and process are presented and analyzed. The GPU model is capable of simulating a SNN with up to two million neurons. GPU and CPU results are directly verified and found to match exactly.
Keywords :
biocomputing; digital simulation; graphics processing units; neural nets; CPU; GPU device; OpenCL framework; Radeon HD 7970; SNN; biologically-realistic multiprecision spiking neural network simulation; graphical processing units; scalable multiprecision simulation; Biological system modeling; Computational modeling; Graphics processing unit; Mathematical model; Neurons; Numerical models; Synchronization; GPU implementation; OpenCL; high precision; spiking neural network simulation;
Conference_Titel :
Neural Networks (IJCNN), The 2012 International Joint Conference on
Conference_Location :
Brisbane, QLD
Print_ISBN :
978-1-4673-1488-6
Electronic_ISBN :
2161-4393
DOI :
10.1109/IJCNN.2012.6252440
