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

该奖项支持使用多核计算架构（例如现代 GPU 和 Cell BE）来加速引力波物理领域的建模和数据分析计算的研究。有效利用此类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 在许多重要方面都有所不同。因此，对于计算科学家来说，对多种加速器硬件类型进行编程通常会成为一项艰巨的任务，涉及大量冗余软件开发。开放计算语言 (OpenCL) 由 Nvidia（该 GOALI 奖的行业合作伙伴）和 Apple（以及该项目的合作研究人员）领导，旨在跨平台和供应商中立，并受当前可用的所有主要计算机硬件（CPU、Nvidia 和 ATI GPU、IBM Cell BE 等）支持。 OpenCL 可能为计算科学家提供了一个机会，以显着减少代码开发来探索多种加速器技术。该项目的主要目标是在各种不同的硬件架构上对用于科学计算（数值建模和数据分析）的 OpenCL（以及密切相关的框架）进行仔细评估。将对这些软件开发框架进行详细的研究，从移植当前科学代码的难易程度开始，到在各种不同的硬件架构上可以获得的最终性能水平。与传统的多核处理器相比，这种方法可以显着提高性能和成本效益。更具体地说，该项目将重点研究这种基于 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 等多核架构有望以相对较低的成本显着提升数值建模和数据分析任务的性能；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个不需要这种冗余工作的框架。这将使计算科学家有机会以更少的努力探索多种计算机架构。具体成果将是基于 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。该 GOALI 奖项让研究生参与研究，因此直接有助于学生培训，尤其是对计算机行业的强烈关注。此外，拟议的研究建立了学术界和工业界之间的合作。这项工作涉及将知识、技能和技术从工业界直接转移到学术界。行业顾问将帮助培训研究生使用 OpenCL 等尖端软件开发框架，从而培养高就业率的工程师和科学家。该项目的成果以及所开发的任何通用代码或软件库将通过该项目的专用网站免费分发。

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.