Vectorization of Local Search for Solving Flow-shop Scheduling Problem on Xeon Phi™ MIC Co-processors

被引：0
|
作者：
Vaillant, Gautier [1 ]
Mezmaz, Mohand [1 ]
Tuyttens, Daniel [1 ]
Melab, Nouredine [2 ]
机构：
[1] Univ Mons, Math & OR Dept, B-7000 Mons, Belgium
[2] Univ Lille 1, CNRS CRIStAL, Inria Lille Nord Europe, F-59655 Villeneuve Dascq, France
来源：
2016 INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING & SIMULATION (HPCS 2016) | 2016年
关键词：
MIC architecture; Intel Xeon Phi; Permutation problems; Flow-Shop Problem; SIMD; Vectorization; Local search;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper aims to propose a vectorizable cost function for the permutation flow-shop problem (PFSP) with the makespan criterion. This vectorization has been tested on a Xeon Phi core, using a local search. Indeed, Xeon Phi co-processors require vectorization in order to get the best performance from the device. Taillard's benchmark instances are used for the validation of the algorithm. The obtained results show that vectorization is more efficient as the number of jobs and the number of machines increase. Speedups up to 4.5x are recorded.
引用
收藏
页码：729 / 735
页数：7
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