%0 Journal Article %1 minkovich_hrlsim:_2014 %A Minkovich, K. %A Thibeault, C.M. %A O'Brien, M.J. %A Nogin, A. %A Cho, Y. %A Srinivasa, N. %D 2014 %J IEEE Transactions on Neural Networks and Learning Systems %K gpu simulation %N 2 %P 316--331 %R 10.1109/TNNLS.2013.2276056 %T HRLSim: A High Performance Spiking Neural Network Simulator for GPGPU Clusters %V 25 %X Modeling of large-scale spiking neural models is an important tool in the quest to understand brain function and subsequently create real-world applications. This paper describes a spiking neural network simulator environment called HRL Spiking Simulator (HRLSim). This simulator is suitable for implementation on a cluster of general purpose graphical processing units (GPGPUs). Novel aspects of HRLSim are described and an analysis of its performance is provided for various configurations of the cluster. With the advent of inexpensive GPGPU cards and compute power, HRLSim offers an affordable and scalable tool for design, real-time simulation, and analysis of large-scale spiking neural networks.

@article{minkovich_hrlsim:_2014, abstract = {Modeling of large-scale spiking neural models is an important tool in the quest to understand brain function and subsequently create real-world applications. This paper describes a spiking neural network simulator environment called {HRL} Spiking Simulator ({HRLSim).} This simulator is suitable for implementation on a cluster of general purpose graphical processing units ({GPGPUs).} Novel aspects of {HRLSim} are described and an analysis of its performance is provided for various configurations of the cluster. With the advent of inexpensive {GPGPU} cards and compute power, {HRLSim} offers an affordable and scalable tool for design, real-time simulation, and analysis of large-scale spiking neural networks.}, added-at = {2014-01-19T15:21:31.000+0100}, author = {Minkovich, K. and Thibeault, {C.M.} and {O'Brien}, {M.J.} and Nogin, A. and Cho, Y. and Srinivasa, N.}, biburl = {https://www.bibsonomy.org/bibtex/2de5a333bab780da37e5089becd86f432/neurokernel}, doi = {10.1109/TNNLS.2013.2276056}, interhash = {4212636ce96904d93757d3ce3af0cc7d}, intrahash = {de5a333bab780da37e5089becd86f432}, issn = {2162-{237X}}, journal = {{IEEE} Transactions on Neural Networks and Learning Systems}, keywords = {gpu simulation}, number = 2, pages = {316--331}, shorttitle = {{HRLSim}}, timestamp = {2014-01-19T15:21:31.000+0100}, title = {{HRLSim:} A High Performance Spiking Neural Network Simulator for {GPGPU} Clusters}, volume = 25, year = 2014 }