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symmetric eigenvalue problem

Dalal Sukkari

Ph.D., Applied Mathematics and Computational Science

polar decomposition svd dense linear algebra High Performance Computing symmetric eigenvalue problem

Research interests and present research project. Dalal's research centers on a new high performance implementation of the QR-based Dynamically Weighted Halley iterations (QDWH) to compute the polar decomposition and its application to the SVD (QDWH-SVD). She has introduced a high performance QDWH-SVD implementation on multicore architecture enhanced with multiple GPUs, and on distributed memory based on the state-of-the-art vendor-optimized numerical library ScaLAPACK, and has presented the first asynchronous, task-based formulation of the polar decomposition QDWH and its corresponding

Communication Theory Lab (CTL)

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