MRI-R2: Acquisition of a GPU-Based Cluster for Plasma, High-Energy Density and Computational Science at UCLA

该奖项是根据2009年美国复苏和再投资法案（公法111-5）资助的。主要为视频游戏设计的专用计算机处理器，称为图形处理单元（gpu），通过以低成本和低功耗提供大量计算资源，具有革新科学计算的潜力。加州大学洛杉矶分校将建立一个基于gpu的集群，专注于使用细胞内粒子（PIC）方法进行等离子体模拟。将这个集群连接在一起的网络是精心设计的，因此感兴趣的仿真工具将在其中非常有效地运行。集群本身将由96个双四核（Intel i7）节点组成，每个节点连接两个Nvidia Tesla gpu（总共192个gpu），并将被安置在数字研究与教育研究所（IDRE）内。集群将有三个主要目的。首先，该集群将作为一个测试平台，用于开发新的并行粒子单元（PIC）算法和代码，这些算法和代码可以在多个gpu联网的系统上运行。这些代码应该能在大型国家超级计算机中心的未来计算机上高效运行。其次，该星团将成为在新的粒子加速器技术、聚变能、空间等离子体、天体物理学和基础等离子体科学方面取得突破的工具。第三，该集群将有助于推动加州大学洛杉矶分校计算科学广泛和多样化领域的研究和教育。待研究的等离子体物理课题可能对具有重大社会影响的更广泛领域产生广泛影响，如新型紧凑型加速器技术、聚变能和通信卫星的可靠性。该集群还将具有广泛的教育影响，因为学生将能够解决各种领域的前沿问题，而这些问题以前需要典型的国家实验室的资源。该项目的首席研究员也是加州大学洛杉矶分校数字研究与教育研究所的主任。其中两名联合pi是IDRE的工作人员。通过IDRE，集群和围绕它的活动，其他科学领域的研究人员将学习如何在GPU上进行计算，GPU集群也将用于培训学生跨越一系列基于计算的研究课题。

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).Specialized computer processors, designed primarily for video games, called graphics processing units (GPUs) have the potential to revolutionize scientific computing, by providing large computing resources at low cost and low power. A cluster based on GPUs will be constructed at UCLA focusing on plasma simulations using the particle-in-cell (PIC) method. The network that links this cluster together is carefully designed so that the simulation tools of interest will run very efficiently on it. The cluster itself will consist of 96 dual quad-core (Intel i7) nodes each connected to two Nvidia Tesla GPUs (192 GPUs total) and will be housed within the Institute for Digital Research and Education (IDRE). The cluster will have three main purposes. First, the cluster will serve as a testbed for developing new parallel particle-in-cell (PIC) algorithms and codes to run on systems that have many GPUs networked together. The codes should run efficiently on future computers housed at large national, supercomputer centers. Second, the cluster will be an instrument to enable breakthroughs in new particle accelerator technology, fusion energy, space plasmas, astrophysics, and basic plasma science. Third, the cluster will help to advance research and education in broad and diverse areas of Computational Science at UCLA. The plasma physics subjects to be studied could have a broad impact on a wider range of fields that have a significant societal impact, fields such as new compact accelerator technology, fusion energy, and the reliability of communication satellites. The cluster will also have broad educational impact in that students will be able tackle problems at the cutting edge of a variety of fields, that previously would have required resources typical of a national laboratory. The Principal Investigator on this project is also the Director of the UCLA Institute for Digital Research and Education. Two of the co-PI's are IDRE staff members. Through IDRE, the cluster and the activities centered around it researchers in other science domains will learn how to compute on GPU's and the GPU cluster will also be used to train students across a wide array of computational based research topics.