Enabling the Next Generation of Scalable Clusters

W. Gropp
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Abstract

Clusters revolutionized computing by making supercomputer capabilities widely available. But one of the main drivers of that revolution, the rapid doubling of processor clock rates, ran out of steam several years ago. To maintain (or even increase) the historic rate of improvement in computing power, processor designs are rapidly increasing parallelism at all levels, including more functional units, more cores, and ways to share resources among threads. Heterogeneous designs that use more specialized processors such as GPGPUs are becoming common. The scale of high-end systems is also getting larger, with 1000-core systems becoming commonplace and systems with over 300,000 cores planned for 2011. However, the software and algorithms for these systems are still basically the same as when the cluster revolution began. Drawing on experiences with the sustained PetaFLOPS system, called Blue Waters, to be installed at Illinois in 2011, and with exploratory work into Exascale system designs, this talk will discuss some of the challenges facing the cluster community as scalability becomes increasingly important and reviews some of the developments in algorithms, programming models, and software frameworks that must complement the evolution of cluster hardware.
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启用下一代可扩展集群
集群通过使超级计算机的功能广泛可用,彻底改变了计算。但这场革命的主要推动力之一,处理器时钟速率的快速翻倍,在几年前就已经失去了动力。为了保持(甚至提高)计算能力的历史改进速度,处理器设计正在迅速提高所有级别的并行性,包括更多的功能单元、更多的内核以及在线程之间共享资源的方式。使用更专业的处理器(如gpgpu)的异构设计正变得越来越普遍。高端系统的规模也越来越大,1000核的系统越来越普遍,2011年计划有超过30万核的系统。然而,这些系统的软件和算法与集群革命开始时基本相同。根据2011年将在伊利诺斯州安装的名为Blue Waters的持续PetaFLOPS系统的经验,以及对Exascale系统设计的探索性工作,本演讲将讨论随着可扩展性变得越来越重要,集群社区面临的一些挑战,并回顾算法、编程模型和软件框架的一些发展,这些发展必须补充集群硬件的发展。
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