Implementations of main algorithms for generalized eigenproblem on GPU accelerator

Authors:
Yonghua Zhao;Jian Zhang;Xuebin Chi
Affiliations:
Supercomputing Center, Computer Network Information Center, Chinese Academy of Sciences, Beijing, China;Supercomputing Center, Computer Network Information Center, Chinese Academy of Sciences, Beijing, China;Supercomputing Center, Computer Network Information Center, Chinese Academy of Sciences, Beijing, China
Venue:
ICSI'12 Proceedings of the Third international conference on Advances in Swarm Intelligence - Volume Part II
Year:
2012

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Abstract

A generalized eigensystem problem is usually transformed, utilizing Cholesky decomposition, to a standard eigenproblem. The latter is then solved efficiently by a matrix reduction approach based on Householder tridiagonalization method. We present parallel implementation of an integrated transformation-reduction algorithm on GPU accelerator using CUBLAS. Experimental results clearly demonstrate the potential of data-parallel coprocessors for scientific computations. When comparing against the CPU implementation, the GPU implementations achieve above 16-fold and 26-fold speedups in double precision for reduction and transformation respectively.