Paper Info
Title
Improvement of Workload Balancing Using Parallel Loop Self-Scheduling on Intel Xeon Phi
Abstract
In this paper, we will examine how to improve workload balancing on a computing cluster by a parallel loop self-scheduling scheme. We use hybrid MPI and OpenMP parallel programming in C language. The block partition loop is according to the performance weighting of compute nodes. This study implements parallel loop self-scheduling use Xeon Phi, with its characteristics to improve workload balancing between heterogeneous nodes. The parallel loop self-scheduling is composed of the static and dynamic allocation. A weighting algorithm is adopted in the static part while the well-known loop self-scheduling scheme is adopted in the dynamic part. In recent years, Intel promotes its new product Xeon Phi coprocessor, which is similar to the x86 architecture coprocessor. It has about 60 cores and can be regarded as a single computing node, with the computing power that cannot be ignored. In our experiment, we will use a plurality of computing nodes. We compute four applications, i.e., Matrix multiplication, sparse matrix multiplication, Mandelbrot set computation, and the circuit satisfiability problem. Our results will show how to do the weight allocation and how to choose a scheduling scheme to achieve the best performance in the parallel loop self-scheduling.
Year
DOI
Venue
2015
https://doi.org/10.1007/s11227-017-2068-9
The Journal of Supercomputing
Keywords
Field
DocType
Intel Xeon Phi,Many-core,OpenMP,MPI,Parallel loop,Self-scheduling
x86,Computer science,Xeon Phi,Scheduling (computing),Loop fission,Parallel computing,Coprocessor,Dynamic priority scheduling,Matrix multiplication,Computer cluster
Conference
Volume
Issue
ISSN
73
11
0920-8542
Citations 
PageRank 
References 
1
0.36
9
Authors
5
Name
Order
Citations
PageRank
Chao-Wei Huang110.36
Zong-Yue Wan210.36
Chao-Tung Yang31196139.50
Jung-Chun Liu423333.10
Shuo-Tsung Chen55812.62