research-article

Defining future platform requirements for e-Science clouds

Authors:

Lavanya Ramakrishnan,

Keith R. Jackson,

Shane Canon,

Shreyas Cholia,

John ShalfAuthors Info & Claims

SoCC '10: Proceedings of the 1st ACM symposium on Cloud computing

Pages 101 - 106

https://doi.org/10.1145/1807128.1807145

Published: 10 June 2010 Publication History

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Abstract

Cloud computing has evolved in the commercial space to support highly asynchronous web 2.0 applications. Scientific computing has traditionally been supported by centralized federally funded supercomputing centers and grid resources with a focus on bulk-synchronous compute and data-intensive applications. The scientific computing community has shown increasing interest in exploring cloud computing to serve e-Science applications, with the idea of taking advantage of some of its features such as customizable environments and on-demand resources. Magellan, a recently funded cloud computing project is investigating how cloud computing can serve the needs of mid-range computing and future data-intensive scientific workloads. This paper summarizes the application requirements and business model needed to support the requirements of both existing and emerging science applications, as learned from the early experiences on Magellan and commercial cloud environments. We provide an overview of the capabilities of leading cloud offerings and identify the existent gaps and challenges. Finally, we discuss how the existing cloud software stack may be evolved to better meet e-Science needs, along with the implications for resource providers and middleware developers.

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Saad AEl-Mahdy AEl-Shishiny HChillet D(2019)Performance Modeling of MPI-based Applications on Cloud Multicore ServersProceedings of the Rapid Simulation and Performance Evaluation: Methods and Tools10.1145/3300189.3300194(1-6)Online publication date: 21-Jan-2019
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Chandra SVarde AWang J(2019)A Hive and SQL Case Study in Cloud Data Analytics2019 IEEE 10th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)10.1109/UEMCON47517.2019.8992925(0112-0118)Online publication date: Oct-2019
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Defining future platform requirements for e-Science clouds

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Information

Published In

SoCC '10: Proceedings of the 1st ACM symposium on Cloud computing

June 2010

264 pages

ISBN:9781450300360

DOI:10.1145/1807128

General Chair:
Joseph M. Hellerstein
University of California, Berkeley, USA
,
Program Chairs:
Surajit Chaudhuri
Microsoft Research, USA
,
Mendel Rosenblum
Stanford University, USA

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 10 June 2010

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SOCC '10

Sponsor:

SOCC '10: ACM SIGMOD-SIGOPS Workshop on Cloud Computing in conjunction with SIGMOD 2010

June 10 - 11, 2010

Indiana, Indianapolis, USA

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Overall Acceptance Rate 169 of 722 submissions, 23%

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Cited By

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Saad AEl-Mahdy A(2020)HPCCloud Seer: A Performance Model Based Predictor for Parallel Applications on the CloudIEEE Access10.1109/ACCESS.2020.29928808(87978-87993)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.2992880
Saad AEl-Mahdy AEl-Shishiny HChillet D(2019)Performance Modeling of MPI-based Applications on Cloud Multicore ServersProceedings of the Rapid Simulation and Performance Evaluation: Methods and Tools10.1145/3300189.3300194(1-6)Online publication date: 21-Jan-2019
https://dl.acm.org/doi/10.1145/3300189.3300194
Chandra SVarde AWang J(2019)A Hive and SQL Case Study in Cloud Data Analytics2019 IEEE 10th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)10.1109/UEMCON47517.2019.8992925(0112-0118)Online publication date: Oct-2019
https://doi.org/10.1109/UEMCON47517.2019.8992925
Mohammadi MBazhirov TGuan S(2018)Comparative benchmarking of cloud computing vendors with high performance linpackProceedings of the 2nd International Conference on High Performance Compilation, Computing and Communications10.1145/3195612.3195613(1-5)Online publication date: 15-Mar-2018
https://dl.acm.org/doi/10.1145/3195612.3195613
Caballer MZala SGarcía ÁMoltó GFernández PVelten M(2018)Orchestrating Complex Application Architectures in Heterogeneous CloudsJournal of Grid Computing10.1007/s10723-017-9418-y16:1(3-18)Online publication date: 1-Mar-2018
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González PPardo XPenas DTeijeiro DBanga JDoallo R(2017)Using the Cloud for parameter estimation problemsProceedings of the 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing10.1109/CCGRID.2017.58(797-806)Online publication date: 14-May-2017
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Galante Gda Rosa Righi R(2017)Exploring Cloud Elasticity in Scientific ApplicationsCloud Computing10.1007/978-3-319-54645-2_4(101-125)Online publication date: 3-Jun-2017
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Atif MKobayashi RMenadue BLin CSanderson MWilliams A(2016)Breaking HPC Barriers with the 56GbE CloudProcedia Computer Science10.1016/j.procs.2016.07.17493(3-11)Online publication date: 2016
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