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Abstract: A Novel Hybrid CPU-GPU Generalized Eigensolver for Electronic Structure Calculations Based on Fine Grained Memory Aware Tasks.

, , , , and . SC Companion, page 1338-1339. IEEE Computer Society, (2012)

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LU Factorization of Small Matrices: Accelerating Batched DGETRF on the GPU., , , , , and . HPCC/CSS/ICESS, page 157-160. IEEE, (2014)Divide and Conquer Symmetric Tridiagonal Eigensolver for Multicore Architectures., , , and . IPDPS, page 51-60. IEEE Computer Society, (2015)On the Development of Variable Size Batched Computation for Heterogeneous Parallel Architectures., , , and . IPDPS Workshops, page 1249-1258. IEEE Computer Society, (2016)High-Performance Tensor Contractions for GPUs., , , , , , , , , and 1 other author(s). ICCS, volume 80 of Procedia Computer Science, page 108-118. Elsevier, (2016)Towards batched linear solvers on accelerated hardware platforms., , , , and . PPOPP, page 261-262. ACM, (2015)A Framework for Batched and GPU-Resident Factorization Algorithms Applied to Block Householder Transformations., , , , and . ISC, volume 9137 of Lecture Notes in Computer Science, page 31-47. Springer, (2015)Weighted dynamic scheduling with many parallelism grains for offloading of numerical workloads to multiple varied accelerators., , , , , and . ScalA@SC, page 5:1-5:8. ACM, (2015)High-performance Cholesky factorization for GPU-only execution., , , and . GPGPU@PPoPP, page 42-52. ACM, (2017)PLASMA: Parallel Linear Algebra Software for Multicore Using OpenMP., , , , , , , , , and 5 other author(s). ACM Trans. Math. Softw., 45 (2): 16:1-16:35 (2019)Batched matrix computations on hardware accelerators based on GPUs., , , , and . IJHPCA, 29 (2): 193-208 (2015)