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

高端计算（HEC）机器上的/O正日益成为致命的性能瓶颈。然而，传统的HEC执行范例是以计算为中心的，并且在解决数据密集型应用的关键I/O问题方面具有固有的局限性。在本项目中，PI提出了一种解耦的执行范式（DEP）来解决I/O瓶颈问题。DEP是第一个使用户能够单独识别和处理数据密集型操作的范例。建议的研究的目标是三个方面：1）理解的执行范式的要求，从数据为中心的观点，2）研究的可行性，提出的解耦执行范式，和3）提供一个部分实现的原型DEP及其相关的系统设计，以支持前两个目标。已经确定了几个技术障碍，其中包括系统架构，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，以评估新提出的解耦执行范例。

/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.