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High-throughput computing / Many-task computing / Scheduling / Apache Hadoop / Job scheduler / Oracle Grid Engine / Cloud computing / Concurrency control / Scalability / Computing / Concurrent computing / Parallel computing


Achieving Efficient Distributed Scheduling with Message Queues in the Cloud for Many-Task Computing and High-Performance Computing Iman Sadooghi, Sandeep Palur, Ajay Anthony, Isha Kapur, Karthik Belagodu, Pankaj Purandar
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Document Date: 2014-06-28 17:54:55

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City

Boston / New York / Washington / DC / /

Company

Distributed Systems / Amazon / Petascale Systems / Google / HTC / /

Country

United States / /

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Facility

University of Chicago / NoSQL key/value store / National Institute of Standards / Illinois Institute of Technology / /

IndustryTerm

performance computing / job execution systems / scientific applications / grid computing scales / cloud computing building blocks / art systems / complicated systems / job management systems / non-trivial load balancing algorithms / virtualization technology / computing / scientific computing / cloud services / /

MusicGroup

Sparrow / MATRIX / /

OperatingSystem

Linux / Mac OSX / Microsoft Windows / /

Organization

Illinois Institute of Technology / Ioan Raicu Department of Computer Science / University of Chicago / NASA HPC / /

Person

Sandeep Palur / Ajay Anthony / Job Scheduling Strategies / Kiran Ramamurty / Iman Sadooghi / Pankaj Purandare / /

Position

manager / administrator / Major / scheduler / forward / Private / controller / worker and the worker / /

Product

Franklin / /

ProgrammingLanguage

Cilk / XML / DC / /

ProvinceOrState

Illinois / New York / Massachusetts / /

Technology

virtualization technology / XML / Linux / API / shared memory / Operating Systems / encryption / load balancing / Java / non-trivial load balancing algorithms / Parallel Processing / /

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http /

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