Abstract
In this paper, we present preliminary results on a complete eigensolver based on the Yau and Lu method. We first give an overview of this invariant subspace decomposition method for dense symmetric matrices followed by numerical results and work in progress of a distributed-memory implementation. We expect that the algorithm's heavy reliance on matrix-matrix multiplication, coupled with FFT should yield a highly parallelizable algorithm. We present performance results for the dominant computation kernel on the Intel Paragon.
This work is partly supported by the European project KIT 108 and Eureka Euro-TOPS project.
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Domas, S., Tisseur, F. (1997). Parallel implementation of a symmetric eigensolver based on the Yau and Lu method. In: Palma, J.M.L.M., Dongarra, J. (eds) Vector and Parallel Processing — VECPAR'96. VECPAR 1996. Lecture Notes in Computer Science, vol 1215. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-62828-2_117
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DOI: https://doi.org/10.1007/3-540-62828-2_117
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