ITR: Intelligent High-Performance Computing on Toys

ITR：玩具智能高性能计算

• 批准号: 0219597
• 负责人: Daniel Reed
• 金额: $ 40万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-09-01 至 2004-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0219597&HistoricalAwards=false
• 关键词: ITR; Intelligent; Performance; Computing; Toys

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.

价格低于300美元的游戏机，性能与PC不相上下或超过PC，以及最近只有高端可视化超级计算机才能发现的图形功能，是另一个计算时代的先锋。 在玩具上玩电脑此外，市场力量和激烈的供应商竞争（例如， 微软、任天堂和索尼等公司）继续推动这些游戏平台的技术创新和性能改进，从而在新领域创造研发激励和部署机会。 该提案概述了一项研究计划，以评估科学计算和高分辨率可视化的游戏系统的效用和性能。 这种游戏系统的评估将基于一套自适应性能分析工具的开发，这些工具支持离线和在线性能优化，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PlayStation 2 Linux软件的增强。 此外，我们目前正在与索尼进行谈判，以获得并在NCSA部署大型PlayStation2集群，用于实验评估和科学可视化。 我们的玩具软件计算研究计划集中在三个领域：（a）离线，应用程序和系统软件的多级性能检测，（B）在线，多版本代码执行的自适应选择，以及（c）使用大规模科学应用程序和可视化软件的实验评估。新的硬件性能测量、仪表化科学和图形库以及性能衍生工具，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，将迭代性能调优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，并使用模糊逻辑规则库生成调整位置和选项的建议，该模糊逻辑规则库包含Sony PlayStation2的性能调整建议。