CAREER: Autotuning Foundations for Exascale Computing

职业：百亿亿次计算的自动调整基础

• 批准号: 0953100
• 负责人: Richard Vuduc
• 金额: $ 46万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-04-15 至 2015-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0953100&HistoricalAwards=false
• 关键词: CAREER; Autotuning; Foundations; Exascale; Computing

The goal of this research is to discover novel foundational principlesfor developing highly-efficient and reliable software that can achievesustainable performance on the exascale computing platforms expected by2020. Such platforms will deliver three orders of magnitude beyondtoday?s systems; harnessing this raw computational power couldrevolutionize our modeling and understanding of critical phenomena inareas like climate modeling, energy, medicine, sustainability,cosmology, engineering design, and massive-scale data analytics. Yet,developing software for exascale systems is a tremendous challengebecause the hardware is complex and it is not believed that the mostproductive ?high-level? software development environments (e.g.,programming languages and libraries) will be able to effectively exploitthese exascale systems.The investigator aims to address this challenge by using automatedtuning (autotuning) to eliminate the low performance traditionallyassociated with high-level programming models. This research (a)develops new model-driven frameworks for tuning parallel algorithms anddata structures, going beyond existing techniques that focus onlow-level code tuning; and (b) studies autotuning for programs expressedin high-level programming models, with the aim of eliminating theperformance gap. Concomitant with this research, the PI will create anew practicum course: The HPC Garage. The HPC Garage physicallyco-locates interdisciplinary teams in a social collaborative lab space;the teams engage in a year-long competition, called the XD Prize, todevelop highly scalable algorithms and software for NSF TeraGrid?snext-generation XD facilities. The HPC Garage also hosts summer internsin Georgia Tech?s Computing Research Undergraduate Intern SummerExperience (CRUISE) program, whose mission is to encourage students,especially those from underrepresented groups, to pursue graduatedegrees in computing.

这项研究的目标是发现新的基本原则，以开发高效和可靠的软件，可以在预计到2020年的exascale计算平台上保持性能。这样的平台将提供三个数量级超越今天？的系统;利用这种原始的计算能力可以彻底改变我们对气候建模、能源、医学、可持续性、宇宙学、工程设计和大规模数据分析等领域关键现象的建模和理解。然而，为exascale系统开发软件是一个巨大的挑战，因为硬件是复杂的，它不被认为是最有效的？高级别？软件开发环境（例如，研究人员的目标是通过使用自动调优（autotuning）来消除传统上与高级编程模型相关的低性能来解决这一挑战。本研究（a）开发了新的模型驱动的并行算法和数据结构调优框架，超越了现有的关注低级代码调优的技术;（B）研究了在高级编程模型中表达的程序的自动调优，目的是消除性能差距。伴随着这项研究，PI将创建新的实习课程：HPC车库。HPC Garage物理上将跨学科团队共同安置在社会协作实验室空间中;这些团队参加为期一年的比赛，称为XD奖，为NSF TeraGrid开发高度可扩展的算法和软件。下一代XD设备HPC车库还举办夏季实习格鲁吉亚理工学院？的计算研究本科实习生暑期体验（CRUISE）计划，其使命是鼓励学生，特别是那些来自代表性不足的群体，追求研究生学位的计算。