XPS: Full: CCA: Enhancing Scalability and Energy Efficiency in Extreme-Scale Parallel Systems through Application-Aware Communication Reduction

XPS：完整：CCA：通过减少应用程序感知通信来增强超大规模并行系统的可扩展性和能源效率

• 批准号: 1438286
• 负责人: David Lilja
• 金额: $ 66.6万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2020-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1438286&HistoricalAwards=false
• 关键词: XPS; Full; CCA; Enhancing; Scalability

The high-performance computing systems available today are far from meeting the performance and energy efficiency targets necessary to satisfy the needs of future computing systems. With processor clock frequencies leveling off over the past several years, the only way to achieve the expected levels of performance within the same physical size and the same or lower energy requirements is to have more processors computing in parallel. However, increasing concurrency among the processors increases inter-processor communication, which then becomes the critical bottleneck. This work proposes an application-centric approach to minimize communication-induced overheads in order to enable extreme scalability. The implicit fault tolerance of future parallel applications can be exploited to mitigate the degraded locality and increased communication costs of highly concurrent systems while ensuring an acceptable level of application output quality. This work specifically focuses on (i) how data to be transferred can be compressed, and possibly discarded, and (ii) how communication and synchronization can be avoided or relaxed in certain application contexts, all while maintaining an acceptable level of output quality for the specific application. The intellectual merit of this work stems from its exploration of cross-layer communication and synchronization techniques that exploit application characteristics to significantly reduce the cost of communication and synchronization. This approach will enable a wider array of applications to exploit parallelism and thereby increase their scalability. This work will enable extreme scalability of domain-specific applications executing on large-scale computing systems by quantifying the costs and benefits associated with application-aware communication and synchronization, designing application-aware scalable communication and synchronization primitives, developing software to support application-aware scalable communication, and designing new micro-architectural and system supports for application-aware scalable communication.The broader impact of this research lies in significantly reducing the costs of communication and synchronization for a wide spectrum of applications and consequently enabling new levels of parallel scalability and energy efficiency across a range of application programs. This project will produce open source tools for analyzing and enhancing the scalability of parallel applications, and will provide new opportunities for both graduate and undergraduate students to participate in cutting-edge computer systems research.

当今可用的高性能计算系统远非满足满足未来计算系统需求所需的性能和能源效率目标。 在过去几年中，随着处理器时钟频率升级，实现相同物理大小和相同或较低能量需求的预期性能水平的唯一方法是并行更多的处理器计算。 但是，处理器之间的并发增加会增加处理器间的通信，然后成为关键的瓶颈。 这项工作提出了一种以申请为中心的方法，以最大程度地减少通信引起的开销，以实现极端的可扩展性。 可以利用未来平行应用的隐式容忍度，以减轻降级的当地和增加高度并发系统的通信成本，同时确保可接受的应用程序输出质量水平。 这项工作特别关注（i）如何压缩和可能丢弃数据的数据，以及（ii）如何在某些应用程序上下文中避免或放松沟通和同步，同时在特定应用程序中保持可接受的输出质量水平。 这项工作的智力优点源于其探索跨层通信和同步技术，这些技术利用应用程序特征可显着降低沟通和同步成本。 这种方法将使更广泛的应用程序能够利用并行性，从而提高其可扩展性。 这项工作将通过量化与应用程序意识到的沟通和同步相关的成本和收益，设计可扩展性的沟通和同步的软件，开发可实现的应用程序的沟通，并为应用程序的沟通提供了显着的范围，从而，可以在大规模计算系统上执行的领域特定应用程序的极端可伸缩性。多种应用程序的沟通成本和同步成本，因此在一系列应用程序中实现了新的并行可扩展性和能源效率的水平。 该项目将生产开源工具，用于分析和增强并行应用的可扩展性，并为研究生和本科生提供新的机会，以参与尖端的计算机系统研究。