About Dalal Sukkari 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 Events Presented Events Dec 8 - Dec 14, 2019 SLATE: Design of a Modern Distributed and Accelerated Dense Linear Algebra Library Dalal Sukkari, Ph.D., Applied Mathematics and Computational Science Dec 11, 16:00 - 17:00 B2 L5 R5220 The SLATE (Software for Linear Algebra Targeting Exascale) library is being developed to provide fundamental dense linear algebra capabilities for current and upcoming distributed high-performance systems, both accelerated CPU–GPU based and CPU based.
SLATE: Design of a Modern Distributed and Accelerated Dense Linear Algebra Library Dalal Sukkari, Ph.D., Applied Mathematics and Computational Science Dec 11, 16:00 - 17:00 B2 L5 R5220 The SLATE (Software for Linear Algebra Targeting Exascale) library is being developed to provide fundamental dense linear algebra capabilities for current and upcoming distributed high-performance systems, both accelerated CPU–GPU based and CPU based.
Engage ORCID ShareClipboard Related Sites Hierarchical Computations on Manycore Architectures (HiCMA) Applied Mathematics and Computational Science (AMCS) Related Content Articles 2 Events 1 Related Links Also view Publications in the KAUST Repository. Polar project on Github
