Towards Dynamic Autotuning of SpMV in CUSP Library
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14610%2F24%3A00137324" target="_blank" >RIV/00216224:14610/24:00137324 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/IPDPSW63119.2024.00012" target="_blank" >http://dx.doi.org/10.1109/IPDPSW63119.2024.00012</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/IPDPSW63119.2024.00012" target="_blank" >10.1109/IPDPSW63119.2024.00012</a>
Alternative languages
Result language
angličtina
Original language name
Towards Dynamic Autotuning of SpMV in CUSP Library
Original language description
Sparse matrix-vector product (SpMV) is a central operation in many iterative methods for solving linear systems and, as such, is an attractive candidate for acceleration on the GPU. However, the performance of the SpMV kernel can vary depending both on the target architecture as well as on the sparsity pattern of the matrix. Thus, to achieve optimal performance, the implementation might need to be adjusted for each particular matrix and architecture. This can be achieved through dynamic autotuning, a method that can optimize a source code during program runtime. In this paper, we present a dynamic autotuning of SpMV kernel included in a production-quality CUSP library. We identify and implement tuning parameters and use the Kernel Tuning Toolkit framework for autotuning of SpMV working with the DIA and ELL sparse matrix formats. The dynamic autotuning integration is fully transparent to the library users - it can be activated just by re-compiling software using our tunable version of the CUSP. The proposed autotuned library is evaluated by comparing it with the original CUSP kernels on a set of representative matrices and by examining the contribution of autotuning. The results show that the autotuned kernels can reach up to about 16.9 × speedup compared to a fixed implementation.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/LM2023054" target="_blank" >LM2023054: e-Infrastructure CZ</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)
ISBN
9798350364613
ISSN
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e-ISSN
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Number of pages
9
Pages from-to
14-22
Publisher name
IEEE
Place of publication
San Francisco, USA
Event location
Mauritius
Event date
Jan 1, 2024
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001284697300084