IMPROVING PERFORMANCE IN HPC SYSTEM UNDER POWER CONSUMPTIONS LIMITATIONS

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Published: Apr 20, 2019
DOI: https://doi.org/10.26483/ijarcs.v10i2.6397
Keywords:
HPC, Exascale computing, Massive parallelism, Intra-node communication, Inter-node communication.

Main Article Content

Muhammad Usman Ashraf
GC Women University. Sialkot, Pakistan
Amna Arshad
GC Women University. Sialkot, Pakistan
Rabia Aslam
GC Women University. Sialkot, Pakistan

Abstract

Today's High-Performance Computing (HPC) systems require significant usage of "supercomputers" and extensive parallel processing approaches for solving complicated computational tasks at the Petascale level of performance (1015 calculations per second). The next breakthrough in the computing revolution is the Exascale level of performance that is 1018 calculations per second-a remarkable achievement in computing that will have a fathomless influence towards everyday life. Current supercomputers can't achieve such a high level of performance under power dissipation constraints. Even though the Exascale performance can be achieved by multiplying the number of cores according to Exascale computing system constraints, the challenge of power consumption still persists. However, the primary focus of this study is to analyse how to enhance performance under power consumption limitations for emerging technologies. Leading to objectives, the current study presents a comprehensive analysis of existing strategies that can be considered to enhance performance and reducing power for emerging Exascale computing system. Consequently, we have suggested a massive parallel programming mechanism which is promising to achieve HPC Exascale system goals.

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Vol. 10 No. 2 (2019): March-April 2019
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Author Biographies

Muhammad Usman Ashraf, GC Women University. Sialkot, Pakistan

Department of Computer Science and Information Technology

Amna Arshad, GC Women University. Sialkot, Pakistan

Department of Computer Science and Information Technology

Rabia Aslam, GC Women University. Sialkot, Pakistan

Department of Computer Science and Information Technology

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