Model-based optimization of MPDATA on Intel Xeon Phi through load imbalancing

Alexey Lastovetsky, Lukasz Szustak, Roman Wyrzykowski
University College Dublin, Belfield, Dublin 4, Irleand
arXiv:1507.01265 [cs.DC], (5 Jul 2015)


   title={Model-based optimization of MPDATA on Intel Xeon Phi through load imbalancing},

   author={Lastovetsky, Alexey and Szustak, Lukasz and Wyrzykowski, Roman},






Download Download (PDF)   View View   Source Source   



Load balancing is a widely accepted technique for performance optimization of scientific applications on parallel architectures. Indeed, balanced applications do not waste processor cycles on waiting at points of synchronization and data exchange, maximizing this way the utilization of processors. In this paper, we challenge the universality of the load-balancing approach to optimization of the performance of parallel applications. First, we formulate conditions that should be satisfied by the performance profile of an application in order for the application to achieve its best performance via load balancing. Then we use a real-life scientific application, MPDATA, to demonstrate that its performance profile on a modern parallel architecture, Intel Xeon Phi, significantly deviates from these conditions. Based on this observation, we propose a method of performance optimization of scientific applications through load imbalancing. We also propose an algorithm that finds the optimal, possibly imbalanced, configuration of a data parallel application on a set of homogeneous processors. This algorithm uses functional performance models of the application to find the partitioning that minimizes its computation time but not necessarily balances the load of the processors. We show how to apply this algorithm to optimization of MPDATA on Intel Xeon Phi. Experimental results demonstrate that the performance of this carefully optimized load-balanced application can be further improved by 15% using the proposed load-imbalancing optimization.
Rating: 0.5/5. From 1 vote.
Please wait...

* * *

* * *

Featured events

Hida Takayama, Japan

The Third International Workshop on GPU Computing and AI (GCA), 2018

Nagoya University, Japan

The 5th International Conference on Power and Energy Systems Engineering (CPESE), 2018

MediaCityUK, Salford Quays, Greater Manchester, England

The 10th International Conference on Information Management and Engineering (ICIME), 2018

No. 1037, Luoyu Road, Hongshan District, Wuhan, China

The 4th International Conference on Control Science and Systems Engineering (ICCSSE), 2018

Nanyang Executive Centre in Nanyang Technological University, Singapore

The 2018 International Conference on Cloud Computing and Internet of Things (CCIOT’18), 2018

HGPU group © 2010-2018 hgpu.org

All rights belong to the respective authors

Contact us: