Data transfer matters for GPU computing

Yusuke Fujii, Takuya Azumi, Nobuhiko Nishio, Shinpei Kato, Masato Edahiro

研究成果

45 被引用数 (Scopus)

抄録

Graphics processing units (GPUs) embrace many-core compute devices where massively parallel compute threads are offloaded from CPUs. This heterogeneous nature of GPU computing raises non-trivial data transfer problems especially against latency-critical real-time systems. However even the basic characteristics of data transfers associated with GPU computing are not well studied in the literature. In this paper, we investigate and characterize currently-achievable data transfer methods of cutting-edge GPU technology. We implement these methods using open-source software to compare their performance and latency for real-world systems. Our experimental results show that the hardware-assisted direct memory access (DMA) and the I/O read-and-write access methods are usually the most effective, while on-chip micro controllers inside the GPU are useful in terms of reducing the data transfer latency for concurrent multiple data streams. We also disclose that CPU priorities can protect the performance of GPU data transfers.

本文言語English
ホスト出版物のタイトルProceedings - 2013 19th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2013
出版社IEEE Computer Society
ページ275-282
ページ数8
ISBN(印刷版)9781479920815
DOI
出版ステータスPublished - 2013
イベント2013 19th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2013 - Seoul, Korea, Republic of
継続期間: 2013 12 152013 12 18

出版物シリーズ

名前Proceedings of the International Conference on Parallel and Distributed Systems - ICPADS
ISSN(印刷版)1521-9097

Conference

Conference2013 19th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2013
国/地域Korea, Republic of
CitySeoul
Period13/12/1513/12/18

ASJC Scopus subject areas

  • ハードウェアとアーキテクチャ

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