计算机工程Issue(2)：292-297,6.DOI:10.3969/j.issn.1000-3428.2015.02.056
面向节点异构GPU集群的编程框架
Programming Framework for Node Heterogeneous GPU Cluster
摘要
Abstract
The mainly used programming method for heterogeneous GPU cluster is hybrid MPI/CUDA or its simple deformation. However,because of its transparency to underlying architecture when using hybrid MPI/CUDA to write code for heterogeneous GPU cluster,programmers tend to need detailed knowledge of the hardware resources,which makes the program more complicated and less portable. This paper presents Distributed Parallel Programming Framework ( DISPAR) , a new programming framework for node-level heterogeneous GPU cluster based on data flow model. DISPAR framework contains two sub-systems, StreamCC and StreamMAP. StreamCC is a code conversion tool which coverts DISPAR code into hybrid MPI/CUDA code. StreamMAP is a run-time system which can detect heterogeneous computing resources and map the tasks to appropriate computing units automatically. Experimental results show that the methods can make efficient use of the computing resources and simplify the programming on heterogeneous GPU cluster. Besides,it has better portability and scalability as the code does not rely on the execution platform.关键词
GPU集群/异构/分布式并行编程框架/代码转换/任务分配/可移植性Key words
GPU cluster/heterogeneous/Distributed Parallel Programming Framework ( DISPAR )/code conversion/task assignment/portability分类
信息技术与安全科学引用本文复制引用
盛冲冲,胡新明,李佳佳,吴百锋..面向节点异构GPU集群的编程框架[J].计算机工程,2015,(2):292-297,6.基金项目
复旦大学ASIC和系统国家重点实验室基金资助项目 （）
华为创新研究计划基金资助项目。 （）
