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Performance Models for Data Transfers: A Case Study with Molecular Chemistry Kernels

Abstract : In distributed memory systems, it is paramount to develop strategies to overlap the data transfers between memory nodes with the computations in order to exploit their full potential. In this paper, we consider the problem of determining the order of data transfers between two memory nodes for a set of independent tasks with the objective of minimizing the makespan. We prove that, with limited memory capacity, the problem of obtaining the optimal data transfer order is NP-complete. We propose several heuristics to determine this order and discuss the conditions that might be favorable to different heuristics. We analyze our heuristics on traces obtained by running two molecular chemistry kernels, namely, Hartree-Fock (HF) and Coupled Cluster Singles Doubles (CCSD), on 10 nodes of an HPC system. Our results show that some of our heuristics achieve significant overlap for moderate memory capacities and resulting in makespans that are very close to the lower bound.
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https://hal.inria.fr/hal-02431877
Contributor : Lionel Eyraud-Dubois <>
Submitted on : Wednesday, January 8, 2020 - 11:16:04 AM
Last modification on : Friday, January 10, 2020 - 1:43:24 AM
Long-term archiving on: : Friday, April 10, 2020 - 12:21:58 AM

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Suraj Kumar, Lionel Eyraud-Dubois, Sriram Krishnamoorthy. Performance Models for Data Transfers: A Case Study with Molecular Chemistry Kernels. ICPP 2019 - 48th International Conference on Parallel Processing, Aug 2019, Kyoto, Japan. ⟨10.1145/3337821.3337921⟩. ⟨hal-02431877⟩

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