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Evaluating performance and portability of high-level programming models: Julia, Python/Numba, and Kokkos on exascale nodes.

, , , , , , , , , and . IPDPS Workshops, page 373-382. IEEE, (2023)

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DMA++: On the Fly Data Realignment for On-Chip Memories., , , , , and . IEEE Trans. Computers, 61 (2): 237-250 (2012)A Methodology to Build Models and Predict Performance-Power in CMPs., , and . ICPP Workshops, page 193-202. IEEE Computer Society, (2015)Coarse grain parallelization of deep neural networks.. PPoPP, page 1:1-1:12. ACM, (2016)Evaluating performance and portability of high-level programming models: Julia, Python/Numba, and Kokkos on exascale nodes., , , , , , , , , and . IPDPS Workshops, page 373-382. IEEE, (2023)Abisko: Deep codesign of an architecture for spiking neural networks using novel neuromorphic materials., , , , , , , , , and 7 other author(s). Int. J. High Perform. Comput. Appl., 37 (3-4): 351-379 (July 2023)Compute units in OpenMP: Extensions for heterogeneous parallel programming., and . Concurr. Comput. Pract. Exp., (2024)Adaptive and Speculative Memory Consistency Support for Multi-core Architectures with On-Chip Local Memories., , , , and . LCPC, volume 5898 of Lecture Notes in Computer Science, page 218-232. Springer, (2009)sKokkos: Enabling Kokkos with Transparent Device Selection on Heterogeneous Systems using OpenACC., , , , , and . HPC Asia, page 23-34. ACM, (2024)KokkACC: Enhancing Kokkos with OpenACC., , , , and . WACCPD@SC, page 32-42. IEEE, (2022)