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Improving Cloud Storage Network Bandwidth Utilization of Scientific Applications
University of Edinburgh, United Kingdom.
RIKEN Center for Computational Science Japan.
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Software and Computer systems, SCS.ORCID iD: 0000-0001-5452-6794
KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for High Performance Computing, PDC.ORCID iD: 0000-0002-5020-1631
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2023 (English)In: Proceedings of the 7th Asia-Pacific Workshop on Networking, APNET 2023, Association for Computing Machinery (ACM) , 2023, p. 172-173Conference paper, Published paper (Refereed)
Abstract [en]

Cloud providers began to provide managed services to attract scientific applications, which have been traditionally executed on supercomputers. One example is AWS FSx for Lustre, a fully managed parallel file system (PFS) released in 2018. However, due to the nature of scientific applications, the frontend storage network bandwidth is left completely idle for the majority of its lifetime. Furthermore, the pricing model does not match the scalability requirement. We propose iFast, a novel host-side caching mechanism for scientific applications that improves storage bandwidth utilization and end-to-end application performance: by overlapping compute and data writeback through inexpensive local storage. iFast supports the Massage Passing Interface (MPI) library that is widely used by scientific applications and is implemented as a preloaded library. It requires no change to applications, the MPI library, or support from cloud operators. We demonstrate how iFast can accelerate the end-to-end time of a representative scientific application Neko, by 13-40%.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM) , 2023. p. 172-173
National Category
Computer Systems Computer Sciences
Identifiers
URN: urn:nbn:se:kth:diva-338993DOI: 10.1145/3600061.3603122ISI: 001147804500029Scopus ID: 2-s2.0-85173833099OAI: oai:DiVA.org:kth-338993DiVA, id: diva2:1808729
Conference
7th Asia-Pacific Workshop on Networking, APNET 2023, Jun 29 - Jun 30 2023, Hong Kong, China,
Note

Part of ISBN 9798400707827

QC 20231101

Available from: 2023-11-01 Created: 2023-11-01 Last updated: 2024-02-27Bibliographically approved

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Podobas, ArturJansson, NiclasMarkidis, Stefano

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