GOALI: An Exploration of the Use of OpenCL for Numerical Modeling and Data Analysis

GOALI：使用 OpenCL 进行数值建模和数据分析的探索

• 批准号: 1016906
• 负责人: Gaurav Khanna
• 金额: $ 16.65万
• 依托单位: University of Massachusetts, Dartmouth
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1016906&HistoricalAwards=false
• 关键词: GOALI; Exploration; Use; OpenCL; Numerical

This award supports research on using many-core compute architectures, such as modern GPUs and the Cell BE, for accelerating modeling and data analysis computations in the area of gravitational wave physics. A significant challenge in making effective use of such accelerator hardware is that they typically require specialized and vendor-specific software development. For example, Nvidia GPUs use the CUDA SDK, while the Cell BE uses the IBM Cell SDK, and these SDKs differ in many important ways. Thus, programming multiple accelerator hardware types can often become a difficult task for a computational scientist involving considerable redundant software development. The Open Computing Language (OpenCL), led by Nvidia (the industry partner on this GOALI award) and Apple (with a collaborating researcher on this project) is designed to be cross-platform and vendor neutral, and is supported on all the major computer hardware currently available (CPUs, Nvidia & ATI GPUs, IBM Cell BE, etc). OpenCL may give computational scientists a chance to explore several accelerator technologies with significantly less code development. The main goal of this project is to perform a careful evaluation of OpenCL (and closely related frameworks) for scientific computing (numerical modeling and data analysis) on a variety of different hardware architectures. A detailed investigation of these software development frameworks will be performed, starting with the ease of porting current scientific code, to the final performance levels that can be obtained on various different hardware architectures. This approach could yield significantly higher performance and cost-effectiveness when compared with traditional multi-core processors. More specifically, the project will focus on investigating this OpenCL-based optimization approach for projects in numerical relativity and gravitational wave data analysis. Preliminary work (based on CUDA and Cell SDKs) performed by the PI has yielded promising results.Many-core architectures such as GPU and Cell BE, promise significant performance gains for numerical modeling and data analysis tasks at a relatively low cost; however, programming such hardware accelerators can involve considerable redundant software development. Since human resources are often the most expensive and constrained aspects of code development, it would be highly desirable to make use of a framework in which such redundant work is unnecessary. It would give computational scientists a chance to explore multiple computer architectures with less effort. A specific outcome will be OpenCL-based optimization gravitational physics codes to make an immediate impact on the gravitational wave data analysis and source modeling communities. This GOALI award involves graduate students in the research and therefore contributes directly to student training, especially with a strong computer industry focus. In addition, the proposed research establishes collaborations between academia and industry. The work involves direct transfer of knowledge, skill and technology from industry to academia. The industry advisors will help to train the graduate students in cutting-edge software development frameworks like OpenCL, thus generating highly employable engineers and scientists. The outcome of the project and any resulting general purpose code or software libraries that are developed, will be freely distributed via the project's dedicated website.

该奖项支持使用众核计算架构的研究，例如现代GPU和Cell BE，以加速引力波物理领域的建模和数据分析计算。有效利用这种加速器硬件的一个重大挑战是，它们通常需要专门的和特定于供应商的软件开发。例如，Nvidia GPU使用CUDA SDK，而Cell BE使用IBM Cell SDK，这些SDK在许多重要方面有所不同。因此，对多个加速器硬件类型进行编程对于涉及相当多的冗余软件开发的计算科学家来说常常可能变成困难的任务。开放计算语言（OpenCL）由Nvidia（该GOALI奖项的行业合作伙伴）和Apple（与该项目的合作研究员）领导，旨在跨平台和供应商中立，并在所有主要计算机上都受到支持当前可用的硬件（CPU、Nvidia ATI GPU、IBM Cell BE等）。OpenCL可能会给计算科学家一个机会，以显着更少的代码开发来探索几种加速器技术。该项目的主要目标是在各种不同的硬件架构上对OpenCL（以及密切相关的框架）进行科学计算（数值建模和数据分析）的仔细评估。将对这些软件开发框架进行详细调查，从移植当前科学代码的容易程度开始，到可以在各种不同硬件架构上获得的最终性能水平。与传统的多核处理器相比，这种方法可以显著提高性能和成本效益。更具体地说，该项目将专注于研究这种基于OpenCL的优化方法，用于数值相对论和引力波数据分析项目。PI进行的初步工作（基于CUDA和Cell SDK）已经取得了可喜的成果。GPU和Cell BE等众核架构有望以相对较低的成本实现数值建模和数据分析任务的显著性能提升;然而，对此类硬件加速器进行编程可能涉及大量冗余软件开发。由于人力资源通常是代码开发中最昂贵和最受限制的方面，因此非常希望使用一种不需要这种冗余工作的框架。它将给计算科学家一个机会，以更少的努力探索多种计算机架构。一个具体的成果将是基于OpenCL的优化引力物理代码，对引力波数据分析和源建模社区产生直接影响。这个GOALI奖涉及研究生的研究，因此直接有助于学生的培训，特别是与强大的计算机行业的重点。此外，拟议的研究建立了学术界和工业界之间的合作。这项工作涉及从工业界向学术界直接转让知识、技能和技术。行业顾问将帮助培训研究生在尖端的软件开发框架，如OpenCL，从而产生高就业的工程师和科学家。该项目的成果以及由此产生的任何通用代码或开发的软件库将通过该项目的专用网站免费发布。