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Increasing SpMV Energy Efficiency Through Compression: A study of how format, input and platform properties affect the energy efficiency of Compressed Sparse eXtended
Norwegian University of Science and Technology, Faculty of Information Technology, Mathematics and Electrical Engineering, Department of Computer and Information Science.
2013 (English)MasteroppgaveStudent thesis
Abstract [en]

This work is a continuation and augmentation of previous energy studies of Compressed Sparse eXtended (CSX), a framework for efficiently executing Sparse Matrix-Vector Multiplication (SpMV). CSX was developed by the CSLab at the National Technical University of Athens (NTUA), and utilizes compression to overcome a significant memory bottleneck inherent in SpMV, thus increasing performance and energy efficiency of its execution. SpMV is notorious within scientific computing for its low performance. However, the problem is unavoidable, as SpMV can be found within several scientific applications. In this work, CSX is tested as the SpMV kernel in a framework implementing the Conjugate Gradient Method (CG), an iterative algorithm for solving specific linear algebra problems. CSX is also evaluated against Compressed Sparse Row (CSR), a storage scheme widely used when executing SpMV. This work augments existing studies by evaluating properties in the formats themselves, in the matrices used as input and in the target platform to gain knowledge on how to maximize the benefits of CSX, as well as for what cases CSX does not prove beneficial. The work also compares the performance of SpMV-execution on a stand-alone server known as the CARD-server to similar execution on the Vilje supercomputer. This is done to evaluate how the differences between these two machines affect the results. Based on the results, it is shown that CSX should be used for matrices larger than the Last Level Cache (LLC) of the target machine and for matrices with high degrees of clustering in their values. The best energy efficiency trade-offs are found at eight threads on dual socket configurations, and this is shown to be related to the amount of physical cores per CPU. Similarly, frequency throttling is shown to increase the energy efficiency of the execution only at high numbers of threads and at the cost of performance. Overall, CSX is shown to obtain higher energy efficiency than CSR for SpMV-execution, given a suitable problem and run configuration. Thus, it is confirmed that CSX can be used to decrease the energy consumption of SpMV applications.

Place, publisher, year, edition, pages
Institutt for datateknikk og informasjonsvitenskap , 2013. , 103 p.
URN: urn:nbn:no:ntnu:diva-22977Local ID: ntnudaim:9692OAI: diva2:655611
Available from: 2013-10-12 Created: 2013-10-12 Last updated: 2013-10-12Bibliographically approved

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