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On the Development of Variable Size Batched Computation for Heterogeneous Parallel Architectures.

, , , and . IPDPS Workshops, page 1249-1258. IEEE Computer Society, (2016)

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With Extreme Computing, the Rules Have Changed., , , , , , , , and . Comput. Sci. Eng., 19 (3): 52-62 (2017)On the parallel scalability of hybrid linear solvers for large 3D problems. (Sur l'extensibilité parallèle de solveurs linéaires hybrides pour des problèmes tridimensionels de grandes tailles).. National Polytechnic Institute of Toulouse, France, (2008)MAGMA templates for scalable linear algebra on emerging architectures., , , , , , , and . Int. J. High Perform. Comput. Appl., (2020)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)Towards batched linear solvers on accelerated hardware platforms., , , , and . PPoPP, page 261-262. ACM, (2015)High-performance Cholesky factorization for GPU-only execution., , , and . GPGPU@PPoPP, page 42-52. ACM, (2017)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)LU Factorization of Small Matrices: Accelerating Batched DGETRF on the GPU., , , , , and . HPCC/CSS/ICESS, page 157-160. IEEE, (2014)Power-aware computing: Measurement, control, and performance analysis for Intel Xeon Phi., , , , , and . HPEC, page 1-7. IEEE, (2017)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)