- Title
- Determining the difficulty of accelerating problems on a GPU
- Creator
- Tristram, Dale, Bradshaw, Karen L
- Subject
- To be catalogued
- Date
- 2014
- Type
- text
- Type
- article
- Identifier
- http://hdl.handle.net/10962/475208
- Identifier
- vital:77784
- Description
- General-purpose computation on graphics processing units (GPGPU) has great potential to accelerate many scientific models and algorithms. However, since some problems are considerably more difficult to accelerate than others, ascertaining the effort required to accelerate a particular problem is challenging. Through the acceleration of three typical scientific problems, seven problem attributes have been identified to assist in the evaluation of the difficulty of accelerating a problem on a GPU. These attributes are inherent parallelism, branch divergence, problem size, required computational parallelism, memory access pattern regularity, data transfer overhead, and thread cooperation. Using these attributes as difficulty indicators, an initial problem difficulty classification framework has been created that aids in evaluating GPU acceleration difficulty. The difficulty estimates obtained by applying the classification framework to the three case studies correlate well with the actual effort expended in accelerating each problem.
- Format
- computer, online resource, application/pdf, 1 online resource (15 pages), pdf
- Publisher
- South African Computer Society (SAICSIT)
- Language
- English
- Relation
- South African Computer Journal, Tristram, D. and Bradshaw, K., 2014. Determining the difficulty of accelerating problems on a GPU. South African Computer Journal, 53(si-1), pp.45-59, South African Computer Journal volume 53 number si-1 p. 45 2014 2313-7835
- Rights
- Publisher
- Rights
- Use of this resource is governed by the terms and conditions of the South African Computer Society (SAICSIT) terms of use (https://saicsit.org.za/terms-and-conditions-of-use/)
- Rights
- Closed Access
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- Visitors: 17
- Downloads: 5
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 | Determining the difficulty of accelerating problems on a GPU.pdf | 830 KB | Adobe Acrobat PDF | View Details Download |