AAD: Software Tool for Asynchronous-Algorithm Development

AAD：异步算法开发软件工具

• 批准号: 0444285
• 负责人: Zhiyuan Li
• 金额: $ 65万
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-01-01 至 2009-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0444285&HistoricalAwards=false
• 关键词: AAD; Software; Tool; Asynchronous; Algorithm

AAD: A Software Tool for Asynchronous-Algorithm DevelopmentZhiyuan Li, Ananth Grama, Ahmed SamehDepartment of Computer SciencesPurdue UniversityProject SummaryIntellectual Merit:Data communication and memory access latency will continue to be the most severeperformance-limiting factor for high-end computing problems. This proposal takes the view that, for a wide rangeof applications, the computation efficiency can be substantially improved by a fundamental change to the data propagation model in parallel algorithms.Many important applications use iterative solvers to solve partial differential equations (PDEs). In such solvers, each data point is iteratively updatedusing the new values of its neighbors.Data values are therefore propagated across the problem domain over the timesteps. Currently, the predominant wayto propagate the data requires the processor to suspend its computation until all data computed at a predetermined time step have arrived from its neighbors.Such a rigid model not onlyincurs a heavy performance penalty due to processor waiting, butit also severely limits the compiler's ability to transform programs to achievemore efficient parallel execution and better data locality. The PIs propose a software tool which supports a new model called the asynchronous model. Under this model, each data point is updated based on whatever the most recent values available from its neighbors, instead of waiting for valuescomputed at a predetermined step. The new model will hence overcomethe difficulties mentioned above. The asynchronous model, nonetheless,may change the convergence rate of the algorithm.Hence, based on the tradeoff between the convergence rate and theparallel execution efficiency,the application programmer should tune the frequency at whichthe data propagation is re-synchronized in order toaccelarate the convergence. The proposed tool will make it easyfor the application programmer to perform such important tuning.Broader Impact:The success of this project will contribute substantially tothe advance of high-end computing.Moreover, it will also make significant educational and outreach impact.The PIs plan to use the proposed software tool in Purdue's educationalcomputational science and engineering (CSE) graduate program. Students and faculty in this program will use the tool in courses on parallel computingand performance evaluation, as well as in research projects that can benefit from fine-tuning performance on high-end parallel computing platforms.The software developed in this project can also be an effective toolin CSE education programs elsewhere.The PIs have a track record of transferring research ideas toindustrial labs and such collaboration will continue to projectpositive influences on high-performance computer industries.This project will also further enhance PIs' ability to engage a broad community of undergraduate students in various disciplines, through Honor Seminars, special mentoring programs and undergraduate research opportunities.

AAD：一种用于异步 - 算法开发的软件工具，li，Ananth Grama，Ahmed Ahmed samehdepartment of Computer Sciencespurdue Universityprodextionsprojectionsprojectionsprojectionsproject summaryIntlectual优点：数据通信和内存访问延迟将继续是最严重的依赖性限制性因素，这是对高质量计算问题的限制性因素。该提案认为，对于广泛的应用程序，可以通过平行算法中数据传播模型的基本变化来大大提高计算效率。许多重要应用都使用迭代求解器来求解部分微分方程（PDES）。在这样的求解器中，每个数据点都迭代地更新了其邻居的新值。因此，数据域在问题域上在时间段上传播。目前，传播数据的主要方式要求处理器暂停其计算，直到从其邻居中到达的所有数据都已经到达。 PIS提出了一个软件工具，该工具支持一种称为异步模型的新模型。在此模型下，每个数据点都基于其邻居可用的最新值进行更新，而不是在预定的步骤中等待价值观。因此，新模型将克服上述困难。尽管如此，异步模型还是可能会根据收敛速率和平行执行效率之间的权衡而改变算法的收敛速率，应用程序程序员应调整数据传播的频率，以使数据传播按顺序进行重新同步，以使促进趋于融合。所提出的工具将使应用程序编程人执行如此重要的调整。Boader的影响：该项目的成功将有助于高端计算的进步。此外，它还将对Purdue的教育学能力科学和工程（CSE）毕业的PIS计划产生重大的教育和外展影响。该计划中的学生和教师将使用该工具在平行计算和绩效评估的课程中以及可以从高端平行计算平台上进行微调绩效受益的研究项目中使用该工具。该项目开发的软件也可以是其他地方的有效工具CSE教育计划。PISPIS具有对工业效果的传播，可以继续进行研究。通过荣誉研讨会，特殊的指导计划和本科研究机会，增强了PIS与本科生的广泛社区的能力。