GASPRNG: GPU accelerated scalable parallel random number generator library

Main Author: CPC, Mendeley
Other Authors: Gao, Shuang, Peterson, Gregory D.
Format: Dataset
Terbitan: Mendeley , 2013
Subjects:
Online Access: https:/data.mendeley.com/datasets/d8367zv8r6
ctrlnum 0.17632-d8367zv8r6.1
fullrecord <?xml version="1.0"?> <dc><creator>CPC, Mendeley</creator><title>GASPRNG: GPU accelerated scalable parallel random number generator library </title><publisher>Mendeley</publisher><description>Abstract Graphics processors represent a promising technology for accelerating computational science applications. Many computational science applications require fast and scalable random number generation with good statistical properties, so they use the Scalable Parallel Random Number Generators library (SPRNG). We present the GPU Accelerated SPRNG library (GASPRNG) to accelerate SPRNG in GPU-based high performance computing systems. GASPRNG includes code for a host CPU and CUDA code for execution o... Title of program: GASPRNG Catalogue Id: AEOI_v1_0 Nature of problem Many computational science applications are able to consume large numbers of random numbers. For example, Monte Carlo simulations are able to consume limitless random numbers for the computation as long as resources for the computing are supported. Moreover, parallel computational science applications require independent streams of random numbers to attain statistically significant results. The SPRNG library provides this capability, but at a significant computational cost. The GASPRNG library p ... Versions of this program held in the CPC repository in Mendeley Data AEOI_v1_0; GASPRNG; 10.1016/j.cpc.2012.12.001 This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2018)</description><subject>Computer Hardware</subject><subject>Software</subject><subject>Programming Languages</subject><subject>Computational Physics</subject><subject>Computational Method</subject><contributor>Gao, Shuang</contributor><contributor>Peterson, Gregory D.</contributor><type>Other:Dataset</type><identifier>10.17632/d8367zv8r6.1</identifier><rights>CPC_SPECIAL</rights><rights/><relation>https:/data.mendeley.com/datasets/d8367zv8r6</relation><date>2013-04-01T11:00:00Z</date><recordID>0.17632-d8367zv8r6.1</recordID></dc>
format Other:Dataset
Other
author CPC, Mendeley
author2 Gao, Shuang
Peterson, Gregory D.
title GASPRNG: GPU accelerated scalable parallel random number generator library
publisher Mendeley
publishDate 2013
topic Computer Hardware
Software
Programming Languages
Computational Physics
Computational Method
url https:/data.mendeley.com/datasets/d8367zv8r6
contents Abstract Graphics processors represent a promising technology for accelerating computational science applications. Many computational science applications require fast and scalable random number generation with good statistical properties, so they use the Scalable Parallel Random Number Generators library (SPRNG). We present the GPU Accelerated SPRNG library (GASPRNG) to accelerate SPRNG in GPU-based high performance computing systems. GASPRNG includes code for a host CPU and CUDA code for execution o... Title of program: GASPRNG Catalogue Id: AEOI_v1_0 Nature of problem Many computational science applications are able to consume large numbers of random numbers. For example, Monte Carlo simulations are able to consume limitless random numbers for the computation as long as resources for the computing are supported. Moreover, parallel computational science applications require independent streams of random numbers to attain statistically significant results. The SPRNG library provides this capability, but at a significant computational cost. The GASPRNG library p ... Versions of this program held in the CPC repository in Mendeley Data AEOI_v1_0; GASPRNG; 10.1016/j.cpc.2012.12.001 This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2018)
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institution Universitas Islam Indragiri
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first_indexed 2020-04-08T08:15:27Z
last_indexed 2020-04-08T08:15:27Z
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