CISE Research Instrumentation: Applications and Programming Environments for Cache-Coherent Distributed Memory Machines

9818308 Singh，Jaswinder PalOstriker，JeremiahPrinceton University高速缓存一致性分布式存储器机器的应用程序和编程环境该研究仪器支持以下方面的研究项目：- 用于在高速缓存一致性DSM架构上计算蛋白质结构确定的并行应用和编程环境，及-系统评估的并行计算及其对软件和硬件的影响。为了支持集成应用-在上述项目的驱动研究，该奖项有助于购买升级到现有的64处理器SGI Origin 2000多处理器的计算机科学和天体物理系与普林斯顿大学普林斯顿等离子体物理实验室一起。 这些设备将用于继续和加强所列的研究项目，并支持计算机科学和等离子体物理实验室之间的新项目。 第一个项目，计算机科学和天体物理学之间的合作，处理的问题，特别是具有挑战性的并行实施，由于相互作用的模型和高度不规则的动态性质的组合。 目标是为一系列计算开发并行算法和实现，开发可推广和可移植的技术，在提供负载平衡的同时保持局部性，扩展现有的并行语言;使用这些语言的运行时系统，构建分区技术和算法库。 第二个项目是CS和斯坦福大学医学院的合作项目，目标相似，模拟结构生物学中固有的缓慢过程。最后一个项目将扩大可用的工作负载集。 SPLASH套件的并行应用程序在关键的新兴应用领域作为基准的体系结构研究，以及测试床的编程语言和编译器。

9818308Singh, Jaswinder PalOstriker, JeremiahPrinceton UniversityApplications and Programming Environments for Cache-Coherent Distributed Memory MachinesThis research instrumentation enables research projects in:- Parallel Applications and Programming Environments for Computational Cosmology on Cache-Coherent DSM Architectures,- Parallel Applications and Programming Environments for Computational Protein Structure Determination on Cache-Coherent DSM Architectures, and- Parallel Workload for System Evaluation and their Implications for Software and Hardware.To support integrated application-driven research in the aforementioned projects, this award contributes to the purchase of an upgrade to an existing 64-processor SGI Origin2000 multiprocessor by the Departments of Computer Science and Astrophysics together with the Princeton Plasma Physics Laboratory at Princeton University. The equipment will be used to continue and enhance the research projects listed and to support new projects between computer science and the Plasma Physics Laboratory. The first project, a collaboration between Computer Science and Astrophysics, deals with problems particularly challenging for parallel implementation due to the combination of interacting models and a highly irregular dynamic nature. The goals are to develop parallel algorithms and implementations for a range of computations, to develop generalizable and portable techniques preserving locality while providing load balance, to extend existing parallel languages; use runtime systems of these languages, to build libraries of partitioning techniques andalgorithms. The second project, a collaboration between CS and the School of Medicine at Stanford University, with similar goals, simulates inherently slow processes in structural biology. The last project will broaden the set of workloads available. The SPLASH suites of parallel applications in critical emerging application areas serve as benchmarks for architectural studies, as well as testbeds for programming languages and compilers.