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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

Parallel implementation of a symmetric eigensolver based on the Yau and Lu method