XPS: FULL: CCA: An Initial Exploration of Architecture and System Support for Sparsity in Science and Engineering Applications

科学计算仍然是高性能计算机系统发展的关键驱动力，因为它的内在价值和推动计算机系统进步的能力使许多要求苛刻的应用受益。该项目是对跨算法、系统和计算机体系结构优化的初步探索性研究，通过结合面向延迟的核心和面向吞吐量的核心的异构系统来提高应用程序性能并降低能耗。这项活动将确定有可能显著推进即将获得实际效用的重要新兴应用程序的优化。使用一种新的自适应计算流体动力学代码作为驱动程序，本研究旨在确定当前和新兴异构系统的优点和瓶颈。通过对现有硬件的测量和对新兴系统和建议系统的详细模拟，该活动将确定协调通信和计算的体系结构机制，这些机制具有显著提高性能和能源效率的潜力。此活动还将开发异构虚拟机模型的初始设计，该模型将虚拟化所建议的硬件机制，同时为应用程序提供足够的物理硬件知识，以优化执行，同时又不会失去虚拟化的抽象优势。

Scientific computing remains a key driving force in the evolution of high- performance computer systems, because of its inherent value and its ability to drive computer-systems advances that benefit many demanding applications. This project is an initial exploratory investigation into optimizations that cut across algorithms, systems, and computer architecture to improve application performance and reduce energy through heterogeneous systems that combine latency-oriented cores and throughput-oriented cores. This activity will identify optimizations with the potential to significantly advance important emerging applications that are on the verge of attaining practical utility.Using a novel adaptive computational fluid dynamics code as a driver, this research seeks to identify the benefits and bottlenecks of both current and emerging heterogeneous systems. Using both measurements on existing hardware and detailed simulation of emerging and proposed systems, this activity will identify architectural mechanisms for coordinating communication and computation with the potential to significantly increase performance and energy efficiency. This activity will also develop an initial design of a heterogeneous virtual machine model that virtualizes proposed hardware mechanisms, yet provides applications with enough knowledge of the physical hardware to optimize execution without losing the abstraction benefits of virtualization.