Earticle

초록

영어

With the wide application of GPU in High Performance Computing, more and more heterogeneous CPU+GPU clusters have been establishedin many fields. But with the comprehensive using of heterogeneous CPU+GPU clusters, workload balancing has become an important problem when the process nodes coordinate with each other, and the execution time of a program on imbalanced clusters resides on the slowest node. Although there are many strategies and algorithms that can solve the problem of workload balancing to some extent, they generally face the problem of high consumption of communication caused by the task migration. In order to make up for the existing deficiencies, this paper proposes a virtual task migration algorithm adapted to GPU clusters on CUDA platform. This algorithm uses virtual task migration to avoid actual data transmission between nodes, so the communication overhead is obviously decreased. At last, this paper performs an actual test using matrix multiplication to verify this algorithm. The experiment results show that compared with static task partitioning, the algorithm proposed in this paper can effectively achieve dynamic workload balancing and reduce the execution time of programs on GPU clusters, thus the algorithm can significantly improve program execution performance of GPU clusters on CUDA platform.

목차

Abstract
 1. Introduction
 2. Related Work
 3. Workload Imbalance
 4. Virtual Task Migration Algorithm
 5. Experimental Results and Analyzation
 6. Conclusion
 References

키워드

저자

• Jianjiang Li [ Department of Computer Science and Technology, University of Science and Technology Beijing, Beijing P.R.China ]
• Yajun Liu [ Department of Computer Science and Technology, University of Science and Technology Beijing, Beijing P.R.China ]
• Peng Zhang [ Department of Computer Science and Technology, University of Science and Technology Beijing, Beijing P.R.China ] Corresponding Author
• Qingsong Miao [ Department of Computer Science and Technology, University of Science and Technology Beijing, Beijing P.R.China ]
• Lei Zhang [ Department of Computer Science and Technology, University of Science and Technology Beijing, Beijing P.R.China ]
• Wei Chen [ Department of Computer Science and Technology, University of Science and Technology Beijing, Beijing P.R.China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Grid and Distributed Computing

• 간기

  격월간

• pISSN

  2005-4262

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605