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Enabling Performance Engineering in Hesse and Rhineland-Palatinate - A Cooperation of the Rhine-Main-Universities and the Technische Universität Kaiserslautern

Enabling Performance Engineering in Hesse and Rhineland-Palatinate - A Cooperation of the Rhine-Main-Universities and the Technische Universität Kaiserslautern
在黑森州和莱茵兰-普法尔茨州实现性能工程——莱茵美因大学和凯泽斯劳滕技术大学的合作
批准号:
320898076
负责人:
Professor Dr. Christian Bischof
金额:
$0.0万
依托单位国家:
德国
项目类别:
Research Grants
财政年份:
2016
资助国家:
德国
项目状态:
已结题
起止时间:
2015-12-31 至 2019-12-31

项目摘要

项目成果

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中文摘要
翻译
该提案的目的是深化服务范围,并在Technische Universität Darmstadt, Goethe-Universität Frankfurt, Johannes-Gutenberg-Universität Mainz(莱茵-美因大学)和Technische Universität Kaiserslautern的基础HPC编程和调整支持中整合现有结构。在这里代表的四个站点中,我们既有来自一流科学的具有挑战性的高性能计算应用程序的丰富池,也有在关键性能相关研究方面建立良好的研究人员,我们希望利用这些研究人员。因此,我们希望在这些大学的科学专业知识与关键用户需求相吻合的领域提供更深入的HPC服务,将GPU性能工程、基于模型的可扩展性分析以及算法稳定性和可重复性方面的专业知识推向性能工程实践。GPU和矢量化性能的问题是至关重要的,因为它与所有HPC架构相关。性能建模是至关重要的,因为没有它,我们就无法在不必要地消耗资源之前识别潜在的性能瓶颈,这是一个对于应用程序的扩展至关重要的问题,特别是对于第3层、第2层和第1层计算中心之间的有效转换。最后,算法稳定性、性能和可重复性的问题在高性能计算模拟的合理性和可信度方面变得越来越重要。所以这个主题的选择绝不是随机的,而是深思熟虑的;项目团队的科学专业知识与HPC用户的实际需求相吻合。在管理层面,我们希望将HPC支持和性能工程的分布式专业知识整合到一个新的组织中,该组织已经在黑森州HPC能力中心和莱茵兰-普法尔茨州的HPC联盟中建立起来,为黑森州和莱茵兰-普法尔茨州所有大学的HPC支持和性能工程活动提供支持。特别是,我们将确保在所有站点提供专门的现场基础级支持,并将提供上述翻译工作的博士后同事与现有的HPC编程和调优人员相结合,从而创建一个充满活力的分布式科学人员小组,该小组具有共享编程和调优的基础知识以及上述主题能力。我们将提供教程、编码研讨会和功能展示来推广我们的特殊功能。为了显示这项工作的价值,我们将定义成功度量标准,并记录和评估所执行的工作。我们相信,通过这种方式,我们创建了一个服务组织,为我们各州的HPC用户提供组织和运营协同效应,并从所涉及的站点的近距离空间中获利。此外,我们将提供一个模型,用于在分布式组织中划分基本的现场HPC支持,并重点支持相关主题。
英文摘要
The objective of this proposal is to deepen the service scope and to mesh existing structures for basic HPC programming and tuning support at the Technische Universität Darmstadt, the Goethe-Universität Frankfurt, the Johannes-Gutenberg-Universität Mainz (the Rhein-Main Universities), and the Technische Universität Kaiserslautern. Among the four sites represented here, we have both a rich pool of challenging HPC applications emanating from first-class science, but also researchers well-established in critical performance-relevant research that we want to capitalize on.Thus, we want to provide more depth in HPC service in areas where scientific expertise at these universities coincides with critical user needs, pushing expertise on GPU performance engineering, model-based scalability analysis, and algorithmic stability and reproducibility into performance engineering practices. The issue of GPU and vectorization performance is crucial, as it is relevant for all HPC architectures. Performance modeling is critical, as without it, we cannot identify potential performance bottlenecks before resources are expended unnecessarily, an issue that is crucial for the scaling-up of applications, and, in particular, the efficient transition between tier-3, tier-2, and tier-1 computing centers. Lastly, the issues of algorithmic stability, performance, and reproducibility are becoming more and more important with respect to the plausibility and credibility of HPC simulations. So this choice of topics is by no means random but deliberate; the scientific expertise of the project team dovetails with real HPC user needs.At a governance level, we want to bundle the distributed expertise for HPC support and performance engineering that has been already established within the Hessian HPC-Competence Center and the Alliance for HPC in Rhineland-Palatinate in a new umbrella organization for the HPC support and performance engineering activities of all universities of Hesse and Rhineland-Palatinate. In particular, we will ensure dedicated on-site basic level support at all sites, and mesh the postdoctoral associates that provide the translational effort described above with already-existing HPC programming and tuning staff, thus creating a vibrant distributed group of scientific staff that has a shared fundamental knowledge of programming and tuning as well as the topical capabilities mentioned above. We will provide tutorials, coding workshops, and capability showcases to push our special capabilities. To show the value of this work, we will define success metrics, and document and evaluate the work performed.We believe that in this fashion, we create a service organization that offers organizational and operational synergies for HPC users in our states, and profits from the close spatial proximity of the sites involved. In addition, we will provide a model for meshing basic on-site HPC support in a distributed organization with focus support for topics of relevance.
期刊论文(12)
专著(0)
科研奖励(0)
会议论文
A usability case study of algorithmic differentiation tools on the ISSM ice sheet model
ISSM 冰盖模型算法微分工具的可用性案例研究
DOI: 10.1080/10556788.2017.1396602
发表时间: 2018
期刊: Optimization Methods and Software
影响因子: 2.2
作者: [Alexander , Bischof, Christian , Sagebaum, Gauger, Nicolas R. , Jurgelucks , Benjamin , Larour , Perez , Gilberto]
通讯作者: Gilberto
Following the Blind Seer - Creating Better Performance Models Using Less Information
跟随盲目的先知 - 使用更少的信息创建更好的性能模型
DOI: 10.1007/978-3-319-64203-1_8
发表时间: 2017
期刊:
影响因子: --
作者: [Patrick Reisert, Alexandru Calotoiu, Sergei Shudler, Felix Wolf]
通讯作者: Felix Wolf
Proceedings of the 22nd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, Austin, TX, USA, February 4-8, 2017
第 22 届 ACM SIGPLAN 并行编程原理与实践研讨会论文集,美国德克萨斯州奥斯汀,2017 年 2 月 4-8 日
DOI: 10.1145/3155284
发表时间: 2017
期刊:
影响因子: --
作者: [Shudler, Sergei, Calotoiu, Alexandru, Hoefler, Torsten]
通讯作者: Torsten
DOI: 10.1109/cse.2018.00012
发表时间: 2018
期刊: 2018 IEEE International Conference on Computational Science and Engineering (CSE)
影响因子: --
作者: [Burger, Bischof, Calotoiu, Wunderer]
通讯作者: Wunderer
共 12 条
    CATWALK - A Quick Development Path for Performance Models
    • 批准号:
      230954187
    • 项目类别:
      Priority Programmes
    • 资助金额:
      $0.0万
    • 财政年份:
      2012
    • 负责人:
      Professor Dr. Christian Bischof
    • 依托单位:
    海外基金