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

高端计算(HEC)计算机上的I/O正日益成为扼杀性能的瓶颈。然而，HEC的传统执行模式是以计算为中心的，在解决数据密集型应用程序的关键I/O问题方面存在固有限制。为了满足高端计算日益增长的I/O需求，迫切需要开发非常规执行范例。在该项目中，PI提出了一种解耦执行范例(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。这项研究的目的有三个：1)从以数据为中心的观点理解执行范例的需求；2)研究所提出的分离执行范例的可行性；3)提供部分实现的DEP原型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，其中包括系统体系结构、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.