ITR: Intelligent High-Performance Computing on Toys

游戏机的价格低于300美元，性能与个人电脑不相上下，甚至超过个人电脑，图形功能最近只有在高端可视化超级计算机上才能找到，它们是又一代计算的先锋。在玩具上进行计算。此外，市场力量和激烈的供应商竞争(例如，微软、任天堂和索尼之间的竞争)继续推动这些游戏平台的技术创新和性能改进，在新领域创造了研发激励和部署机会。该提案概述了一项研究计划，以评估游戏系统在科学计算和高分辨率可视化方面的实用性和性能。对游戏系统的评估将基于开发一套支持离线和在线性能优化的自适应性能分析工具，并将其应用于一套科学和可视化代码。这项工作利用了提议的Red Hat和NCSA软件对PlayStation2 Linux软件的增强。此外，我们目前正在与索尼谈判在NCSA收购和部署大型PlayStation2集群，用于实验评估和科学可视化。我们的计算玩具软件研究计划集中在三个领域：(A)应用程序和系统软件的离线、多级性能检测；(B)在线、自适应地选择多版本代码执行；以及(C)使用大型科学应用程序和可视化软件进行实验评估。新的硬件性能测量、仪表化科学和图形库以及性能导数，所有这些都与我们的SvPablo性能分析基础设施集成在一起，将提供必要的数据，将迭代性能调整从临时风格转变为基于智能反馈和建议的风格。此SvPablo扩展的离线版本将接受来自硬件、软件和库工具的性能指标，并使用包含索尼PlayStation2性能调整建议的模糊逻辑规则库生成调整位置和选项的建议。

Game consoles, with price points below $300, performance rivaling or exceeding that of PCs, and graphics capabilities recently found only on high-end visualization supercomputers, are the vanguard of yet another computing generation . computing on toys. Moreover, market forces and fierce vendor competition (e.g., among Microsoft, Nintendo, and Sony) continue to fuel technical innovation and performance improvements on these game platforms, creating research and development incentives and deployment opportunities in new domains. This proposal outlines a research plan to assess the utility and performance of game systems for both scientific computing and high-resolution visualization. This assessment of game systems will be based on development of a suite of adaptive performance analysis tools that support both offline and online performance optimization and their application to a suite of scientific and visualization codes. This effort leverages proposed Red Hat and NCSA software enhancements to PlayStation2 Linux software. In addition we currently are negotiating with Sony to acquire and deploy a large PlayStation2 cluster at NCSA for experimental assessment and scientific visualization. Our computing on toys software research plan focuses on three areas: (a) offline, multilevel performance instrumentation of applications and system software, (b) online, adaptive selection of multi-version code execution, and (c) experimental assessment using large-scale scientific applications and visualization software. New hardware performance measurements, instrumented scientific and graphics libraries, and performance derivatives, all integrated with our SvPablo performance analysis infrastructure, will provide the requisite data to move iterative performance tuning from an ad hoc style to one based on intelligent feedback and suggestions. The offline version of this SvPablo extension will accept performance metrics from hardware, software, and library instrumentation and generates suggestions for tuning locations and options using a fuzzy logic rule base that embodies performance tuning suggestions for the Sony PlayStation2.