High-performance Implementation of Recurrent Neural Networks on Graphics Processing Units

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F10%3A00177603" target="_blank" >RIV/68407700:21230/10:00177603 - isvavai.cz</a>
Result on the web
—
DOI - Digital Object Identifier
—

Result language
angličtina
Original language name
High-performance Implementation of Recurrent Neural Networks on Graphics Processing Units
Original language description
The evolutionary algorithms work with large sets of individuals. In our case these individuals represent neural networks. The speed of evaluation of the networks is the very crucial factor because it affects the overall speed of the whole evolution process. In this paper we describe our implementation of the fully recurrent neural networks on the general-purpose graphics processing units. We are using the nVidia CUDA technology to accelerate the simulation of the population of the networks. We have created package for Wolfram Mathematica that provides interface to our accelerated simulator from high-level programming environment. Our library supports the client-server architecture, so you can run the simulations on dedicated CUDA-enabled computationalserver and process the results of the simulations on your desktop using the TCP/IP communication protocol. In this paper we present the results of the speedup experiments.
Czech name
—
Czech description
—

Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the 7th EUROSIM Congress on Modelling and Simulation, Vol. 2: Full Papers
ISBN
978-80-01-04589-3
ISSN
—
e-ISSN
—
Number of pages
4
Pages from-to
—
Publisher name
Department of Computer Science and Engineering, FEE, CTU in Prague
Place of publication
Prague
Event location
Praha
Event date
Sep 6, 2010
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
—

Similar results(10)