Using Mixed Precision for Sparse Matrix Computations to Enhance the Performance while Achieving 64-bit Accuracy

Buttari, Alfredo and Dongarra, Jack and Kurzak, Jakub and Luszczek, Piotr and Tomov, Stanimire (2007) Using Mixed Precision for Sparse Matrix Computations to Enhance the Performance while Achieving 64-bit Accuracy. [MIMS Preprint]

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Abstract

By using a combination of 32-bit and 64-bit floating point arithmetic the performance of many sparse linear algebra algorithms can be significantly enhanced while maintaining the 64-bit accuracy of the resulting solution. These ideas can be applied to sparse multifrontal and supernodal direct techniques, and sparse iterative techniques such as Krylov subspace methods. The approach presented here can apply not only to conventional processors but also to exotic technologies such as Field Programmable Gate Arrays (FPGA), Graphical Processing Units (GPU), and the Cell BE processor.

Item Type:	MIMS Preprint
Additional Information:	Appears also as Technical Report UT-CS-06-584, Department of Computer Science, University of Tennessee, Knoxville, TN, USA, November 2006 and LAPACK Working Note 180
Subjects:	MSC 2010, the AMS's Mathematics Subject Classification > 65 Numerical analysis MSC 2010, the AMS's Mathematics Subject Classification > 68 Computer science
Depositing User:	Ms Lucy van Russelt
Date Deposited:	03 Jul 2007
Last Modified:	08 Nov 2017 18:18
URI:	https://eprints.maths.manchester.ac.uk/id/eprint/820

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