Parallel Implementation of the Yau and Lu Method for Eigenvalue Computation

In this paper, parallel extensions of a complete symmetric eigensolver, proposed by Yau and Lu in 1993, are pre sented. First, an overview of this invariant subspace decomposition method for dense symmetric matrices is given, followed by numerical results. Then, works are exposed in progress on distributed-memory implementa tion. The algorithm's heavy reliance on matrix-matrix mul tiplication, coupled with Fast Fourier Transform (FFT), should yield a highly parallelizable algorithm. Finally, performance results for the dominant computation kernel on the Intel Paragon are presented