CSR: Small:Conductor: A Run-Time System for Exascale Computing

在这个十年结束时达到百万亿次计算目标的关键问题之一-如果不是关键问题的话-就是电源问题。 尽管今天的千万亿次系统（其性能至少比预期的千万亿次系统低两个数量级）通常消耗约5兆瓦，但千万亿次系统的目标功率限制为20兆瓦。 单靠硬件改进并不能弥补这一差距，PI正在开发一个名为Conductor的运行时系统来解决电源问题。 Conductor的总体目标是在规定的功率范围内产生接近最佳的应用性能。 首先，PI正在设计和实现一种名为功率调度的新技术，该技术解决了节点间的情况。 Conductor的第二部分通过电源门控解决了节点内的情况，它允许以比当今架构中通常可用的更细粒度的方式关闭单个组件。最后，PI正在研究允许用户通过注释来帮助Conductor的技术，在功率调度和功率门控单独不足以实现高性能的情况下，重要。导体对于在非平凡应用上实现百亿亿级性能至关重要，它将有助于推动实现百亿亿级目标。实现百亿亿级性能是国家的重要优先事项，将影响许多应用领域。 PI还将研究思路整合到本科生和研究生的并行和分布式计算课程中。

One of the critical problems---if not the critical problem---inreaching the exascale computing goal by the end of the decade is thepower problem. Exascale systems have a target power constraint of 20megawatts even though today's petascale systems---which haveperformance at least two orders of magnitude below prospectiveexascale systems---generally consume around 5 megawatts. Hardwareimprovements alone will not bridge this gap.The PI is developing a run-time system called Conductor to address thepower issue. The overall goal of Conductor is to produce near-optimalapplication performance under a prescribed power bound. Conductorcarries this out by allocating power both between and within nodes.First, the PI is designing and implementing a new technique calledpower scheduling, which addresses the inter-node case. The secondpart of Conductor addresses the intra-node case with power gating,which allows powering off of individual components in a morefine-grain manner than is generally available in architectures today.Finally, the PI is investigating techniques to allow users to assistConductor, through annotations, in achieving high performance in caseswhere power scheduling and power gating alone are not sufficient.The impact of the research described in this proposal is significant.Conductor is essential to achieving exascale performance on nontrivialapplications, and it will help push towards the exascale goal.Achieving exascale performance is an important national priority andwill impact many application domains. The PI is also integrating theresearch ideas into both undergraduate and graduate parallel anddistributed computing courses.