FILIPOVIČ, Jiří and Siegfried BENKNER. OpenCL Kernel Fusion for GPU, Xeon Phi and CPU. In Proceedings of IEEE International Symposium on Computer Architecture and High Performance Computing. Florianópolis: IEEE. p. 98-105. ISSN 1550-6533. doi:10.1109/SBAC-PAD.2015.29. 2015.
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Basic information
Original name OpenCL Kernel Fusion for GPU, Xeon Phi and CPU
Name in Czech Fúze OpenCL kernelů pro GPU, Xeon Phi a CPU
Authors FILIPOVIČ, Jiří (203 Czech Republic, guarantor, belonging to the institution) and Siegfried BENKNER (40 Austria).
Edition Florianópolis, Proceedings of IEEE International Symposium on Computer Architecture and High Performance Computing, p. 98-105, 8 pp. 2015.
Publisher IEEE
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher Brazil
Confidentiality degree is not subject to a state or trade secret
Publication form storage medium (CD, DVD, flash disk)
RIV identification code RIV/00216224:14330/15:00083464
Organization unit Faculty of Informatics
ISSN 1550-6533
Doi http://dx.doi.org/10.1109/SBAC-PAD.2015.29
UT WoS 000380430500013
Keywords (in Czech) OpenCL; fúze kernelů; GPU; Xeon Phi; MIC; CPU
Keywords in English OpenCL; kernel fusion; GPU; Xeon Phi; MIC; CPU
Tags firank_B
Tags International impact, Reviewed
Changed by Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 27/8/2019 11:57.
Abstract
Kernel fusion is an optimization method, in which the code from several kernels is composed to create a new, fused kernel. It can push the performance of kernels beyond limits given for their isolated, unfused form. In this paper, we introduce a classification of different types of kernel fusion for both data dependent and data independent kernels. We study kernel fusion on three types of OpenCL devices: GPU, Xeon Phi and CPU. Those hardware platforms have quite different properties, thus, kernel fusion often affects performance in quite different ways. We analyze the impact of kernel fusion on those hardware platforms and show how it can be used to improve performance. Based on our study we also introduce a basic transformation method for generating fused kernels, which has good potential to be automatized.
Links
EE2.3.30.0037, research and development projectName: Zaměstnáním nejlepších mladých vědců k rozvoji mezinárodní spolupráce
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