MPI-RICAL: Data-Driven MPI Distributed Parallelism Assistance with Transformers

Author:

Schneider Nadav1ORCID,Kadosh Tal1ORCID,Hasabnis Niranjan2ORCID,Mattson Timothy2ORCID,Pinter Yuval3ORCID,Oren Gal4ORCID

Affiliation:

1. Ben-Gurion University of the Negev, Israel and IAEC, Israel

2. Intel Labs, United States of America

3. Ben-Gurion University of the Negev, Israel

4. Technion - Israel Institute of Technology, Israel and NRCN, Israel

Funder

This research was supported by the Israeli Council for Higher Education (CHE) via the Data Science Research Center, Ben-Gurion University of the Negev, Israel; Intel Corporation (oneAPI CoE program); and the Lynn and William Frankel Center for Computer Science. Computational support was provided by the NegevHPC project and Intel Developer Cloud.

Publisher

ACM

Reference44 articles.

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2. [n. d.]. ML-Enhanced Code Completion Improves Developer Productivity. https://ai.googleblog.com/2022/07/ml-enhanced-code-completion-improves.html [Online]. [n. d.]. ML-Enhanced Code Completion Improves Developer Productivity. https://ai.googleblog.com/2022/07/ml-enhanced-code-completion-improves.html [Online].

3. [n. d.]. NegevHPC Project. https://www.negevhpc.com. [Online]. [n. d.]. NegevHPC Project. https://www.negevhpc.com. [Online].

4. The Nas Parallel Benchmarks

5. Towards automatic translation of OpenMP to MPI

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Quantifying OpenMP: Statistical Insights into Usage and Adoption;2023 IEEE High Performance Extreme Computing Conference (HPEC);2023-09-25

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