Evaluating the acceleration of typical scientific problems on the GPU

Tristram, Dale; Bradshaw, Karen L

Title: Evaluating the acceleration of typical scientific problems on the GPU
Creator: Tristram, Dale
Creator: Bradshaw, Karen L
Subject: To be catalogued
Date Issued: 2013
Date: 2013
Type: text
Type: book
Identifier: http://hdl.handle.net/10962/477607
Identifier: vital:78103
Identifier: ISBN 9781450321129
Identifier: https://doi.org/10.1145/2513456.2513473
Description: General-purpose computation on graphics processing units (GPGPU) has great potential to accelerate many scientific models and algorithms. However, some problems are considerably more difficult to accelerate than others, and it may be difficult for those new to GPGPU to ascertain the difficulty of accelerating a particular problem. Additionally, problems of different levels of difficulty require varying complexities of optimisations to achieve satisfactory results, and currently there is no clear separation between the different levels of known optimisations, which would be helpful to new users of GPGPU. Through what was learned in the acceleration of three problems, problem attributes have been identified to assist in evaluating the difficulty of accelerating a problem on a GPU. We envisage that with further development, these attributes could form the foundation of a difficulty classification system that could be used to determine whether GPU acceleration is practical for a candidate GPU acceleration problem, aid in identifying appropriate techniques and optimisations, and outline the required GPGPU knowledge.
Format: 10 pages
Format: pdf
Publisher: ACM Digital Library
Language: English
Relation: Tristram, D. and Bradshaw, K., 2013, October. Evaluating the acceleration of typical scientific problems on the GPU. In Proceedings of the South African Institute for Computer Scientists and Information Technologists Conference (pp. 17-26)
Rights: Authors
Rights: Use of this resource is governed by the terms and conditions of the ACM Digital Library (https://libraries.acm.org/digital-library/policies#anchor3)

Hits: 10
Visitors: 9
Downloads: 0

Collections

SDG 09. Industry, Innovation and Infrastructure

RU Department of Computer Science

Bradshaw, Karen Lee (Assoc Prof)

		Thumbnail	File	Description	Size	Format
View Details Download			SOURCE1	Evaluating the acceleration of typical scinetific problems.pdf	945 KB	Adobe Acrobat PDF	View Details Download