Artemis: Automatic Runtime Tuning of Parallel Execution Parameters Using Machine Learning

Author:

Wood Chad,Georgakoudis Giorgis,Beckingsale David,Poliakoff David,Gimenez Alfredo,Huck Kevin,Malony Allen,Gamblin Todd

Publisher

Springer International Publishing

Cited by 8 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. An automated OpenMP mutation testing framework for performance optimization;Parallel Computing;2024-09

2. An Exploration of Global Optimization Strategies for Autotuning OpenMP-based Codes;2024 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW);2024-05-27

3. MUPPET;Proceedings of the 15th International Workshop on Programming Models and Applications for Multicores and Manycores;2024-03-03

4. Efficient Code Region Characterization Through Automatic Performance Counters Reduction Using Machine Learning Techniques;Lecture Notes in Computer Science;2024

5. Performance Optimization using Multimodal Modeling and Heterogeneous GNN;Proceedings of the 32nd International Symposium on High-Performance Parallel and Distributed Computing;2023-08-07

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