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Multiple-tasks on multiple-devices (MTMD): exploiting concurrency in heterogeneous managed runtimes.

, , , , , и . VEE, стр. 125-138. ACM, (2021)

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Hsiao-Mei Juan

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DLS 2019: Proceedings of the 15th ACM SIGPLAN International Symposium on Dynamic Languages, и . ACM, (20.10.2019)Automatically exploiting the memory hierarchy of GPUs through just-in-time compilation., , , и . VEE, стр. 57-70. ACM, (2021)Dynamic application reconfiguration on heterogeneous hardware., , , , , и . VEE, стр. 165-178. ACM, (2019)Multiple-tasks on multiple-devices (MTMD): exploiting concurrency in heterogeneous managed runtimes., , , , , и . VEE, стр. 125-138. ACM, (2021)Towards GPU Accelerated FHE Computations., , , , , , и . CSR, стр. 694-699. IEEE, (2024)Using compiler snippets to exploit parallelism on heterogeneous hardware: a Java reduction case study., и . VMIL@SPLASH, стр. 16-25. ACM, (2018)Programming Heterogeneous Hardware via Managed Runtime Systems, , и . Springer Briefs in Computer Science Springer, (2024)Beehive SPIR-V Toolkit: A Composable and Functional API for Runtime SPIR-V Code Generation., , , , и . VMIL@SPLASH, стр. 61-72. ACM, (2023)Transparent acceleration of Java-based deep learning engines., , , , , , и . MPLR, стр. 73-79. ACM, (2020)Challenges and Proposals for Enabling Dynamic Heterogeneous Execution of Big Data Frameworks., , и . CloudCom, стр. 335-341. IEEE Computer Society, (2018)