Performance Modeling of MPI-based Applications on Cloud Multicore Servers-Reference-Cited by-同舟云学术

Performance Modeling of MPI-based Applications on Cloud Multicore Servers

Published:2019 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Rapid Simulation and Performance Evaluation: Methods and Tools on - RAPIDO '19
language:
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Author:

Saad Abdallah¹,El-Mahdy Ahmed²,El-Shishiny Hisham³

Affiliation:

1. Egypt-Japan University of Science and Technology, New Burj El-Arab, Alexandria and Benha University

2. Egypt-Japan University of Science and Technology, New Burj El-Arab, Alexandria, Egypt and Alexandria University

3. Advanced Technology and IBM Center

Publisher

ACM Press

Reference18 articles.

1. Bradley J. Barnes, Barry Rountree, David K. Lowenthal, Jaxk Reeves, Bronis de Supinski, and Martin Schulz. 2008. A Regression-based Approach to Scalability Prediction. In Proceedings of the 22Nd Annual International Conference on Supercomputing (ICS '08). ACM, New York, NY, USA, 368--377. https://doi.org/10.1145/1375527.1375580

2. Patrick G. Bridges, Matthew G. F. Dosanjh, Ryan Grant, Anthony Skjellum, Shane Farmer, and Ron Brightwell. 2015. Preparing for Exascale: Modeling MPI for Many-core Systems Using Fine-grain Queues. In Proceedings of the 3rd Workshop on Exascale MPI (ExaMPI '15). ACM, New York, NY, USA, Article 5, 8 pages. https://doi.org/10.1145/2831129.2831134

3. NASA Advanced Supercomputing Division. [n. d.]. NASA Parallel Benchmarks Suite. https://www.nas.nasa.gov/publications/npb.html.

4. Ifeanyi P Egwutuoha, Shiping Chen, David Levy, and Rafael Calvo. 2013. Cost-effective Cloud Services for HPC in the Cloud: The IaaS or The HaaS?. In Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA). 217.

5. Ananth Grama, Anshul Gupta, George Karypis, and Vipin Kumar. 2003. Introduction to Parallel Computing. Pearson Education Limited, Chapter Parallel Programming Platforms, 58--60.

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1. HPCCloud Seer: A Performance Model Based Predictor for Parallel Applications on the Cloud;IEEE Access;2020