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Performance Characterization of De Novo Genome Assembly on Leading Parallel Systems.

, , , , , , , and . Euro-Par, volume 10417 of Lecture Notes in Computer Science, page 79-91. Springer, (2017)

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HipMer: an extreme-scale de novo genome assembler., , , , , , , , and . SC, page 14:1-14:11. ACM, (2015)A Study of BFLOAT16 for Deep Learning Training., , , , , , , , , and 9 other author(s). CoRR, (2019)ISA Mapper: A Compute and Hardware Agnostic Deep Learning Compiler., , , , , and . CoRR, (2018)Performance Characterization of De Novo Genome Assembly on Leading Parallel Systems., , , , , , , and . Euro-Par, volume 10417 of Lecture Notes in Computer Science, page 79-91. Springer, (2017)Anatomy of high-performance deep learning convolutions on SIMD architectures., , , , , , and . SC, page 66:1-66:12. IEEE / ACM, (2018)High-Performance Deep Learning via a Single Building Block., , , , , , , , and . CoRR, (2019)Constructing Performance Models for Dense Linear Algebra Algorithms on Cray XE Systems., , , and . CoRR, (2014)MerBench: PGAS Benchmarks for High Performance Genome Assembly., , , , , , , and . PAW@SC, page 5:1-5:4. ACM, (2017)merAligner: A Fully Parallel Sequence Aligner., , , , , and . IPDPS, page 561-570. IEEE Computer Society, (2015)Training Google Neural Machine Translation on an Intel CPU Cluster., , , , , , , and . CLUSTER, page 1-10. IEEE, (2019)