Accurate Modeling Of Parallel Scientific Computations
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Accurate Modeling of Parallel Scientific Computations
Author: National Aeronautics and Space Administration (NASA)
language: en
Publisher: Createspace Independent Publishing Platform
Release Date: 2018-08-10
Scientific codes are usually parallelized by partitioning a grid among processors. To achieve top performance it is necessary to partition the grid so as to balance workload and minimize communication/synchronization costs. This problem is particularly acute when the grid is irregular, changes over the course of the computation, and is not known until load time. Critical mapping and remapping decisions rest on the ability to accurately predict performance, given a description of a grid and its partition. This paper discusses one approach to this problem, and illustrates its use on a one-dimensional fluids code. The models constructed are shown to be accurate, and are used to find optimal remapping schedules. Nicol, David M. and Townsend, James C. Langley Research Center NASA-CR-181756, ICASE-88-58, NAS 1.26:181756, AD-A203533 NAS1-18107; NAS1-18605; AF-AFOSR-0117-88; RTOP 505-90-21-01...
Accurate Modeling of Parallel Scientific Computations
Scientific codes are usually parallelized by partitioning a grid among processors. To achieve top performance it is necessary to partition the grid so as to balance workload and minimize communication/synchronization costs. This problem is particularly acute when the grid is irregular, changes over the course of the computation, and is not known until load-time. Critical mapping and remapping decisions rest on our ability to accurately predict performance, given a description of a grid and its partition. This paper discusses one approach to this problem, and illustrates its use on a one-dimensional fluids code. The models we construct are shown empirically to be accurate, and are used to find optimal remapping schedules. Keywords: Parallel processing; Dynamic remapping; Analytic modeling.