GPU集群请求分发器的体系结构

M. Doost, S. M. Sadjadi, J. R. Da Silva, M. Zamith, M. Joselli, E. Clua
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引用次数: 2

摘要

GPU计算的出现使得许多加速不同类型模拟的策略得以发展。更进一步说,与其只使用一个GPU来处理一个应用程序,还不如使用一组GPU作为解决方案。这些gpu可以位于同一台机器、网络,甚至跨广域网。不幸的是,gpu的分配和管理需要用户额外的努力,如处理gpu之间的数据传输、连接和处理。RDGPUC是一种软件架构,允许公司、机构和其他用户共享他们的GPU资源。通过使用这种体系结构,每个集群都可以拥有自己的软件来管理内部资源,它们只需要开发与RDGPUC交互的小代码。这种新颖的设计为系统带来了灵活性,并允许每个人共享他们的资源,而无需改变他们的GPU集群工具。系统的另一个有趣的部分是允许用户提交来自各种设备和平台的请求。该系统的管理员可以指定资源组和使用资源的特殊时间表。另一方面,终端用户可以使用一个简单的接口在RDGPUC上提交他们的请求,而无需了解GPU集群的内部设计和当前状态。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Architecture of Request Distributor for GPU Clusters
The advent of GPU computing has enabled development of many strategies for accelerating different kinds of simulations. Even further, instead of processing an application by just using one GPU, it is a common to use a collection of GPUs as a solution. These GPUs can be located in the same machine, network, or even across a wide area network. Unfortunately, distribution and management of GPUs requires additional efforts by the user such as deal with data transfer, connection and processing among GPUs. Request distributor for GPU clusters (RDGPUC) is a software architecture which allows companies, institutes and other users to share their GPU resources. By using this architecture, each cluster can have its own software to manage internal resources and they only need to develop small code to interact with RDGPUC. This novel design brings flexibility to the system and allows everyone to share their resources without need to change their GPU cluster tool. Another interesting part of system is to allow users to submit requests from all kind of devices and platforms. Admin of this system is able to specify resource groups and special schedules for using resources. On the other hand, end-users can just use a simple interface to submit their requests on RDGPUC without knowing about internal design and current status of GPU clusters.
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