Towards Performance and Scalability Analysis of Distributed Memory Programs on Large-Scale Clusters-Reference-Cited by-同舟云学术

Towards Performance and Scalability Analysis of Distributed Memory Programs on Large-Scale Clusters

Published:2016-03-12 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 7th ACM/SPEC on International Conference on Performance Engineering
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Author:

Medya Sourav¹,Cherkasova Ludmila²,Magalhaes Guilherme³,Ozonat Kivanc²,Padmanabha Chaitra⁴,Sarma Jiban⁴,Sheikh Imran⁴

Affiliation:

1. University of california, Santa Barbara, Santa Barbara, CA, USA

2. Hewlett Packard Labs, Palo Alto, CA, USA

3. Hewlett Packard Enterprise, Porto Alegre, Brazil

4. Hewlett Packard Enterprise, Bangalore, India

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/2851553.2858669

Reference15 articles.

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3. Graph500. http://www.graph500.org/. Graph500. http://www.graph500.org/.

4. Paraver:Performance Analysis Tools: Details and Intelligence. http://www.bsc.es/computer-sciences/paraver. Paraver:Performance Analysis Tools: Details and Intelligence. http://www.bsc.es/computer-sciences/paraver.

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1. A mathematical model to calculate real cost/performance in software distributed shared memory on computing environments;The Journal of Supercomputing;2017-11-16

2. In-Test Adaptation of Workload in Enterprise Application Performance Testing;Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering Companion;2017-04-18