Highly Reconfigurable Computing Platform for High Performance Computing Infrastructure as a Service: Hi-IaaS
Highly Reconfigurable Computing Platform for High Performance Computing Infrastructure as a Service: Hi-IaaS
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DOI：
10.5220/0006302501350146
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发表时间：
2017
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影响因子：
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通讯作者：
Akihiro Misawa;S. Date;Keichi Takahashi;Takashi Yoshikawa;Masahiko Takahashi;Masaki Kan;Yasuhiro Watashiba;Y. Kido;Chonho Lee;S. Shimojo
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文献类型：
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作者：
Akihiro Misawa;S. Date;Keichi Takahashi;Takashi Yoshikawa;Masahiko Takahashi;Masaki Kan;Yasuhiro Watashiba;Y. Kido;Chonho Lee;S. Shimojo
对于高性能计算（HPC）用户来说，为自己拥有HPC平台变得越来越困难。随着用户对HPC的需求和要求的多样化，HPC系统具有执行不同应用的容量和能力。在本文中，我们提出了一种计算机体系结构，用于动态和及时地提供高性能计算基础设施作为云计算服务，以响应用户对云的底层计算资源的请求。为了获得适应各种HPC作业的灵活性，其中每一个都可能需要一个独特的计算平台，所提出的系统重新配置软件和硬件平台，利用开放网格计算/网格引擎和OpenStack的协同作用。在这项研究中开发的实验系统显示了高度的灵活性，在硬件可重构性，以及高性能的基准应用程序的火花。此外，我们的评估表明，实验系统可以执行两倍的工作，需要一个图形处理单元（GPU），除了消除最坏的情况下，在现实世界中的运行记录，我们的大学的计算机中心在过去半年的资源拥塞。
It has become increasingly difficult for high performance computing (HPC) users to own a HPC platform for themselves. As user needs and requirements for HPC have diversified, the HPC systems have the capacity and ability to execute diverse applications. In this paper, we present computer architecture for dynamically and promptly delivering high performance computing infrastructure as a cloud computing service in response to users’ requests for the underlying computational resources of the cloud. To obtain the flexibility to accommodate a variety of HPC jobs, each of which may require a unique computing platform, the proposed system reconfigures software and hardware platforms, taking advantage of the synergy of Open Grid Scheduler/Grid Engine and OpenStack. An experimental system developed in this research shows a high degree of flexibility in hardware reconfigurability as well as high performance for a benchmark application of Spark. Also, our evaluation shows that the experimental system can execute twice as many as jobs that need a graphics processing unit (GPU), in addition to eliminating the worst case of resource congestion in the real-world operational record of our university’s computer center in the previous half a year.