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GPU-Aware Non-contiguous Data Movement In Open MPI., , , , and . HPDC, page 231-242. ACM, (2016)Bi-objective scheduling algorithms for optimizing makespan and reliability on heterogeneous systems., , , and . SPAA, page 280-288. ACM, (2007)Harnessing GPU tensor cores for fast FP16 arithmetic to speed up mixed-precision iterative refinement solvers., , , and . SC, page 47:1-47:11. IEEE / ACM, (2018)Standards for Graph Algorithm Primitives., , , , , , , , , and 9 other author(s). CoRR, (2014)BlackjackBench: portable hardware characterization., , , , and . SIGMETRICS Perform. Evaluation Rev., 40 (2): 74-79 (2012)Evaluation of Programming Models to Address Load Imbalance on Distributed Multi-Core CPUs: A Case Study with Block Low-Rank Factorization., , , , and . PAW-ATM@SC, page 25-36. IEEE, (2019)Self adaptivity in Grid computing., and . Concurr. Pract. Exp., 17 (2-4): 235-257 (2005)The design and implementation of the parallel out-of-core ScaLAPACK LU, QR, and Cholesky factorization routines., and . Concurr. Pract. Exp., 12 (15): 1481-1493 (2000)Pumma: Parallel universal matrix multiplication algorithms on distributed memory concurrent computers., , and . Concurr. Pract. Exp., 6 (7): 543-570 (1994)Conjugate-gradient eigenvalue solvers in computing electronic properties of nanostructure architectures., , , , and . Int. J. Comput. Sci. Eng., 2 (3/4): 205-212 (2006)