Parallel Data Partitioning Algorithms for Optimization of Data-Parallel Applications on Modern Extreme-Scale Multicore Platforms for Performance and Energy

Data partitioning algorithms aiming to minimize the execution time and the energy of computations in self-adaptable data-parallel applications on modern extreme-scale multicore platforms must address two critical challenges. First, they must take into account the new complexities inherent in these p...

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Bibliographic Details
Published in:	IEEE access Vol. 6; pp. 69075 - 69106
Main Authors:	Manumachu, Ravi Reddy, Lastovetsky, Alexey
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 2018 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Complexity Data parallelism data partitioning Dynamic programming energy Energy consumption energy optimization Fast Fourier transformations Fourier transforms homogeneous multicore CPU clusters load balancing Matrices (mathematics) Multicore processing Multiplication Optimization parallel algorithms Partitioning Partitioning algorithms performance optimization Platforms Run time (computers) Runtime Servers Shape Workload Workloads
ISSN:	2169-3536, 2169-3536
Online Access:	Get full text
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