A Non-intrusive Methodology to Improve the Performance of Parallel Applications in High Performance Computing

The conjugation of High Performance Computing (HPC) and Grid paradigm with applications based on commercial software is one among the major challenges of today e-Infrastructures. Several research communities from either industry or academia need to run high parallel applications based on licensed software over hundreds of CPU cores; a satisfactory fulfillment of such requests is one of the keys for the penetration of this computing paradigm into the industry world and sustainability of Grid infrastructures. This problem has been tackled in the context of the PI2S2 project that created a regional e-Infrastructure in Sicily, the first in Italy over a regional area. Present article will describe the features added in order to integrate an HPC facility into the PI2S2 Grid infrastructure, the adoption of the InifiniBand low-latency net connection, the gLite middleware extended to support MPI/MPI2 jobs, the newly developed license server and the specific scheduling policy adopted. Moreover, it will show the results of some relevant use cases belonging to Computer Fluid-Dynamics (Fluent, OpenFOAM), Chemistry (GAMESS), Astro-Physics (Flash) and Bio-Informatics (ClustalW)).

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The Sicilian Grid Infrastructure for High Performance Computing

Technology Integration Advancements in Distributed Systems and Computing ◽

10.4018/978-1-4666-0906-8.ch013 ◽

2012 ◽

pp. 215-227

Author(s):

Carmelo Marcello Iacono-Manno ◽

Marco Fargetta ◽

Roberto Barbera ◽

Alberto Falzone ◽

Giuseppe Andronico ◽

...

Keyword(s):

High Performance Computing ◽

High Performance ◽

Parallel Applications ◽

Grid Infrastructure ◽

Scheduling Policy ◽

Computing Paradigm ◽

Regional Area ◽

Computer Fluid Dynamics ◽

Grid Infrastructures ◽

Performance Computing

The conjugation of High Performance Computing (HPC) and Grid paradigm with applications based on commercial software is one among the major challenges of today e-Infrastructures. Several research communities from either industry or academia need to run high parallel applications based on licensed software over hundreds of CPU cores; a satisfactory fulfillment of such requests is one of the keys for the penetration of this computing paradigm into the industry world and sustainability of Grid infrastructures. This problem has been tackled in the context of the PI2S2 project that created a regional e-Infrastructure in Sicily, the first in Italy over a regional area. Present paper will describe the features added in order to integrate an HPC facility into the PI2S2 Grid infrastructure, the adoption of the InifiniBand low-latency net connection, the gLite middleware extended to support MPI/MPI2 jobs, the newly developed license server and the specific scheduling policy adopted. Moreover, it will show the results of some relevant use cases belonging to Computer Fluid-Dynamics (Fluent, OpenFOAM), Chemistry (GAMESS), Astro-Physics (Flash) and Bio-Informatics (ClustalW)).

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Implementation and evaluation of the HPC challenge benchmark in the XcalableMP PGAS language

The International Journal of High Performance Computing Applications ◽

10.1177/1094342017698214 ◽

2017 ◽

Vol 33 (1) ◽

pp. 110-123 ◽

Cited By ~ 5

Author(s):

Masahiro Nakao ◽

Hitoshi Murai ◽

Hidetoshi Iwashita ◽

Taisuke Boku ◽

Mitsuhisa Sato

Keyword(s):

High Performance Computing ◽

High Performance ◽

Parallel Applications ◽

Memory Model ◽

Computing Systems ◽

Local View ◽

And Performance ◽

Performance Results ◽

Performance Computing ◽

Do So

To improve productivity for developing parallel applications on high performance computing systems, the XcalableMP PGAS language has been proposed. XcalableMP supports both a typical parallelization under the “global-view memory model” which uses directives and a flexible parallelization under the “local-view memory model” which uses coarray features. The goal of the present paper is to clarify XcalableMP’s productivity and performance. To do so, we implement and evaluate the high performance computing challenge benchmark, namely, EP STREAM Triad, High Performance Linpack, Global fast Fourier transform, and RandomAccess on the K computer using up to 16,384 compute nodes and a generic cluster system using up to 128 compute nodes. We found that we could more easily implement the benchmarks using XcalableMP rather than using MPI. Moreover, most of the performance results using XcalableMP were almost the same as those using MPI.

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Fault Tolerance Techniques for Distributed, Parallel Applications

Innovative Research and Applications in Next-Generation High Performance Computing - Advances in Systems Analysis, Software Engineering, and High Performance Computing ◽

10.4018/978-1-5225-0287-6.ch009 ◽

2016 ◽

pp. 221-252

Author(s):

Camille Coti

Keyword(s):

Fault Tolerance ◽

High Performance Computing ◽

High Performance ◽

Fault Tolerant ◽

Distributed Applications ◽

Parallel Applications ◽

Rollback Recovery ◽

Tolerance Mechanisms ◽

Performance Computing

This chapter gives an overview of techniques used to tolerate failures in high-performance distributed applications. We describe basic replication techniques, automatic rollback recovery and application-based fault tolerance. We present the challenges raised specifically by distributed, high performance computing and the performance overhead the fault tolerance mechanisms are likely to cost. Last, we give an example of a fault-tolerant algorithm that exploits specific properties of a recent algorithm.

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