Towards exascale computing systems

迈向百亿亿次计算系统

• 批准号: 41188-2011
• 负责人: Dimopoulos, Nikitas
• 金额: $ 1.6万
• 依托单位: University of Victoria
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=568838
• 关键词: Towards; exascale; computing; systems

The proposed research program will focus on issues pertaining to Exascale Computing that is, computing systems attaining performance that is 1000x the performance of the present day PFlop/s systems. Specifically, we shall focus on methods that will contribute in the realization of such systems through performance enhancing techniques applicable to interconnection networks, scheduling, and low power design All are critical issues and are researched intensively internationally. In a cluster system, the interconnect plays an important role in delivering data to the computations. Our research program will develop methods that deliver data to the computations carried out by the many cores of the system with a minimum of latency. We shall investigate both the send and the receive sides of the communication channel. At the send side, prediction will allow the hiding of the setting-up-the-channel overhead while at the receiving end, directly injecting the payload to a section of the storage hierarchy that is the closest (and the fastest) to the computation that will consume it ensures minimal delays. Concomitant to the delivering of data to the computation, is the scheduling of these computations especially in the era of many-core processors. For maximum efficiency, one needs to ensure that a computation scheduled on a particular core is not waiting for data, or instructions. Our objective is to develop methods ensuring that computations are optimally scheduled on the available resources. As far as power is concerned, our objective is to develop a design environment that will automatically produce low power systems utilizing the information that is present within the description of the computation. We are developing techniques that identify the portions of the system that are not active during portions of the computation, so they can be switched-off. We are targeting this environment for embedded systems, but also to specialized computation engines that will be part of hybrid nodes as we move to address the challenge of exascale systems.

拟议的研究计划将重点介绍与Exascale计算有关的问题，即计算系统达到当今Pflop/S系统的性能1000倍的计算系统。 具体来说，我们将专注于通过适用于互连网络，调度和低功率设计的性能增强技术来实现此类系统的方法，这都是关键问题，并且在国际上进行了深入的研究。 在集群系统中，互连在向计算传递数据中起着重要作用。我们的研究计划将开发将数据传递到系统的许多核心进行的计算的方法，最少的延迟。我们将调查通信渠道的发送和接收方面。在发送方面，预测将允许在接收端时隐藏设置通道的开销，直接将有效载荷注入存储层次结构的一部分，该部分是最接近（并且是最快）的计算，该计算将确保其确保最小的延迟。 将数据传递给计算的伴随是这些计算的调度，尤其是在多核处理器的时代。为了提高效率，需要确保在特定核心上安排的计算不等待数据或说明。我们的目标是开发方法，以确保计算在可用资源上最佳地安排。 就力量而言，我们的目标是开发一个设计环境，该设计环境将自动利用计算描述中存在的信息自动产生低功率系统。我们正在开发识别在计算部分中不活跃的系统部分的技术，因此可以关闭它们。我们将这种环境用于嵌入式系统，但也针对专门的计算引擎，这些计算引擎将成为混合节点的一部分，因为我们采取了应对Exascale系统的挑战。