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Publication

Title:Investigating Performance Benefits from OpenACC Kernel Directives
Authors:Benjamin Eagan, Gilles Civario, Renato Miceli, 2014
Abstract: OpenACC is a high-level programming model that uses directives for offloading computation to accelerators. This paper explores the benefit of using OpenACC performance tuning directives to manually specify GPU scheduling, versus the scheduling OpenACC applies by default. We performed manual scheduling using gang and vector clauses in a directive, and applied to matrix-matrix multiply and Classical Gram-Schmidt orthonormalisation test cases. We then tested using the NVIDIA M2090 and K20 GPGPUs, in conjunction with both the PGI and CAPS implementations of OpenACC. The speedup realised by tuning the gang and vector values ranged from 1.0 to 3.1 in the test cases examined. This shows that the gang and vector values have a large impact on performance, and in some cases the compilers are able to automatically select ideal gang and vector values.
ICHEC Project:
Publication:Proc. of the 2013 International Conference on Parallel Computing (ParCo 2013). Parallel Computing: Accelerating Computational Science and Engineering (CSE), Advances in Parallel Computing, IOS Press. Munich, Germany. vol 25, p 616-625. March 2014
URL: http://dx.doi.org/10.3233/978-1-61499-381-0-616
Keywords: OpenACC; GPGPU Computing; Software Tuning
Status: Published

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