CSR: Medium: Collaborative Research: Decoupled Execution Paradigm for Data-Intensive High-End Computing

高端计算（HEC）机器上的I/O正日益成为致命的性能瓶颈。然而，HEC的传统执行范式是以计算为中心的，在处理数据密集型应用程序的关键I/O问题方面存在固有的局限性。为了满足高端计算不断增长的I/O需求，非常需要开发非常规的执行范例。在这个项目中，pi提出了一个解耦执行范例（DEP）来解决I/O瓶颈问题。DEP是第一个允许用户分别识别和处理数据密集型操作的范例。本研究的目标有三个方面：1)从以数据为中心的角度理解执行范式需求；2)研究所提出的解耦执行范式的可行性；3)提供部分实现的DEP原型及其相关系统设计，以支持前两个目标。已经确定了几个技术障碍，包括系统架构、编程模型和运行时系统。提出了解决方案，并提供了详细的计划来评估新提出的解耦执行范式。

I/O on High-End Computing (HEC) machines is increasingly becoming the killing performance bottleneck. However, conventional execution paradigms for HEC are computing-centric and have inherent limitations in addressing critical I/O issues of data-intensive applications. There is a great need for developing unconventional execution paradigms to meet the growing I/O demand of high-end computing.In this project, the PIs propose a decoupled execution paradigm (DEP) to address I/O bottleneck issues. DEP is the first paradigm enabling users to identify and handle data-intensive operations separately. The objective of the proposed research is three-fold: 1) understanding the execution paradigm requirement from the data-centric point of view, 2) studying the feasibility of the proposed decoupled execution paradigm, and 3) providing a partially implemented prototyping of DEP and its associated system design to support the first two objectives. Several technical hurdles have been identified, which include system architecture, programming model, and runtime system. Solutions are proposed and detailed plans are provided to evaluate the newly proposed decoupled execution paradigm.