Using MPI in high-performance computing services

Zounmevo, Judicael A.; Kimpe, Dries; Ross, Robert; Afsahi, Ahmad

doi:10.1145/2488551.2488556

Cited by 13 publications

(6 citation statements)

References 12 publications

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“…Utilization of computer cluster is also applied in the networking field. Zounmevo et al use MPI as a network transport for a large-scale [11]. They implemented MPI in three programming tool i.e.…”

Section: Research In Computer Clustermentioning

confidence: 99%

The Optimal High Performance Computing Infrastructure for Solving High Complexity Problem

2016

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Section: Research In Computer Clustermentioning

confidence: 99%

The Optimal High Performance Computing Infrastructure for Solving High Complexity Problem

2016

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“…Indeed MPI already provides functions to build a communicator across multiple applications (MPI_Comm_{connect,accept}, MPI_Port_{open,close}), as applications start and leave. Yet, since an application cannot know when another one will try to contact it, these connection primitives should be made non-blocking, either by extending the MPI standard with MPI_Comm_{iconnect,iaccept} or by calling these functions from a thread (something that is also done in [15]). Such a thread would be required only in coordinator processes, that is, one extra thread per application.…”

Section: Implementation Optionsmentioning

confidence: 99%

CALCioM: Mitigating I/O Interference in HPC Systems through Cross-Application Coordination

Dorier

Antoniu

Ross

et al. 2014

2014 IEEE 28th International Parallel and Distributed Processing Symposium

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Abstract-Unmatched computation and storage performance in new HPC systems have led to a plethora of I/O optimizations ranging from application-side collective I/O to network and disk-level request scheduling on the file system side. As we deal with ever larger machines, the interference produced by multiple applications accessing a shared parallel file system in a concurrent manner becomes a major problem. Interference often breaks single-application I/O optimizations, dramatically degrading application I/O performance and, as a result, lowering machine wide efficiency.This paper focuses on CALCioM, a framework that aims to mitigate I/O interference through the dynamic selection of appropriate scheduling policies. CALCioM allows several applications running on a supercomputer to communicate and coordinate their I/O strategy in order to avoid interfering with one another. In this work, we examine four I/O strategies that can be accommodated in this framework: serializing, interrupting, interfering and coordinating. Experiments on Argonne's BG/P Surveyor machine and on several clusters of the French Grid'5000 show how CALCioM can be used to efficiently and transparently improve the scheduling strategy between two otherwise interfering applications, given specified metrics of machine wide efficiency.

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“…Since MPI is an important standard for HPC communication [10], we evaluate its performance using three different communications patterns: Single Transfer, Parallel Transfer and Collective Communications. We used the same type of virtual machine (VM) instance among four different Azure Data Centers and used the machines at different times, during working hours and during the night.…”

Section: Introductionmentioning

confidence: 99%

Performance Evaluation of Multiple Cloud Data Centers Allocations for HPC

Roloff

Carreno

Valverde-Sánchez

et al. 2017

Communications in Computer and Information Science

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Abstract. This paper evaluates the behavior of the Microsoft Azure G5 cloud instance type over multiple Data Centers. The purpose is to identify if there are major differences between them and to help the users choose the best option for their needs. Our results show that there are differences in the network level for the same instance type in different locations and inside the same location at different times. The network performance causes interference in the applications level, as we could verify in our results.

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Using MPI in high-performance computing services

Cited by 13 publications

References 12 publications

The Optimal High Performance Computing Infrastructure for Solving High Complexity Problem

The Optimal High Performance Computing Infrastructure for Solving High Complexity Problem

CALCioM: Mitigating I/O Interference in HPC Systems through Cross-Application Coordination

Performance Evaluation of Multiple Cloud Data Centers Allocations for HPC

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