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000889157 1001_ $$0P:(DE-HGF)0$$aGupta, Nikunj$$b0
000889157 1112_ $$a2020 IEEE International Conference on Cluster Computing (CLUSTER)$$cKobe$$d2020-09-14 - 2020-09-17$$wJapan
000889157 245__ $$aPerformance Evaluation of ParalleX Execution model on Arm-based Platforms
000889157 260__ $$bIEEE$$c2020
000889157 300__ $$a567-575
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000889157 520__ $$aThe HPC community shows a keen interest in creating diversity in the CPU ecosystem. The advent of Arm-based processors provides an alternative to the existing HPC ecosystem, which is primarily dominated by x86 processors. In this paper, we port an Asynchronous Many-Task runtime system based on the ParalleX model, i.e., High Performance ParalleX (HPX), and evaluate it on the Arm ecosystem with a suite of benchmarks. We wrote these benchmarks with an emphasis on vectorization and distributed scaling. We present the performance results on a variety of Arm processors and compare it with their x86 brethren from Intel. We show that the results obtained are equally good or better than their x86 brethren. Finally, we also discuss a few drawbacks of the present Arm ecosystem.
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000889157 536__ $$0G:(EU-Grant)779877$$aMont-Blanc 2020 - Mont-Blanc 2020, European scalable, modular and power efficient HPC processor (779877)$$c779877$$fH2020-ICT-2017-1$$x1
000889157 536__ $$0G:(DE-Juel1)PHD-NO-GRANT-20170405$$aPhD no Grant - Doktorand ohne besondere Förderung (PHD-NO-GRANT-20170405)$$cPHD-NO-GRANT-20170405$$x2
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000889157 7001_ $$0P:(DE-HGF)0$$aAshiwal, Rohit$$b1
000889157 7001_ $$0P:(DE-Juel1)174207$$aBrank, Bine$$b2$$ufzj
000889157 7001_ $$0P:(DE-HGF)0$$aPeddoju, Sateesh K.$$b3
000889157 7001_ $$0P:(DE-Juel1)144441$$aPleiter, Dirk$$b4$$eCorresponding author$$ufzj
000889157 773__ $$a10.1109/CLUSTER49012.2020.00080
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