首页> 外文会议>2011 8th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology >Multi-level parallelism, global arrays, GPGPU Programming: Unify programming paradigms on Grid computing with efficiency
【24h】

Multi-level parallelism, global arrays, GPGPU Programming: Unify programming paradigms on Grid computing with efficiency

机译:多级并行,全局数组,GPGPU编程:高效地统一网格计算上的编程范例

获取原文
获取外文期刊封面目录资料

摘要

As technology advances, computing resources also gain benefits in many aspects: larger capacity, increased capability as well as rapidity. However, with heterogeneously distributed resources in Grid computing environment, the development an application to fully utilize the resources is a challenge. Especially, the computing resources themselves regularly upgrade their computing power for example by recruiting General Purpose Graphics Processing Unit (GPGPU) resources. The challenge in developing an application on computing environment like that becomes even greater. In this paper, we propose an approach to unify the programming paradigms in Grid computing and GPGPU computing as well as further our investigation on the performance of an application developed on such environment. To maximize its efficiency, the grid application is developed based on multi-level parallelism together with multi-level topology-aware techniques and the Global Arrays toolkit. We have successfully implemented the grid application with the proposed approach and the performance of the application depends directly on how the computing loads are distributed over those resources. The direct portability of a GPGPU application/module in order to be integrated into a comprehensive grid computing code is also observed in our approach.
机译:随着技术的进步,计算资源也从许多方面受益:更大的容量,更高的功能以及更快的速度。但是,对于网格计算环境中的异构分布的资源,开发一种充分利用资源的应用程序是一个挑战。特别地,计算资源本身例如通过招募通用图形处理单元(GPGPU)资源来定期升级其计算能力。在这样的计算环境上开发应用程序的挑战变得更大。在本文中,我们提出了一种统一网格计算和GPGPU计算中的编程范例的方法,并进一步研究了在这种环境下开发的应用程序的性能。为了最大程度地提高效率,网格应用程序是基于多级并行性以及多级拓扑感知技术和“全局阵列”工具包开发的。我们已经使用所提出的方法成功地实现了网格应用程序,并且应用程序的性能直接取决于计算负载如何分布在这些资源上。在我们的方法中,还可以观察到GPGPU应用程序/模块的直接可移植性,以便将其集成到全面的网格计算代码中。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号