RI: Mastodon: A Large-Memory, High-Throughput Simulation Infrastructure

RI：Mastodon：大内存、高吞吐量的模拟基础设施

• 批准号: 0303609
• 负责人: Risto Miikkulainen
• 金额: $ 144.53万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-09-01 至 2008-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0303609&HistoricalAwards=false
• 关键词: RI; Mastodon; Large; Memory; Throughput

Digital simulation is becoming dominant in not only many fields of physical sciences, but computer science as well. Despite the great improvements in processing speed over the past decades, advanced research on large-scale systems requires simulation engines that are more powerful than the average desktop workstation.The Department of Computer Sciences at the University of Texas at Austin will assemble an infrastructure for performing large-scale, memory-intensive simulations. Called Mastodon, this infrastructure will consist of a large number of rack-mounted Linux/x86 servers, each with multiple processors and several gigabytes of physical memory. Leveraged by industrial and university matching funds, we anticipate scaling Mastodon to 418 processors and nearly a terabyte of DRAM. The cluster will utilize both distributed batch scheduling using the Condor job management software, as well as soft partitioning for timing and parallel experiments.This infrastructure will service the needs of a majority of our department's faculty. The projects utilizing Mastodon include the areas of systems (specifically, architecture, compilers, and run-time systems), network algorithms, computational biology, multi-agent robotics, and formal verification. In each of these areas, Mastodon makes multiple projects feasible, whereas with conventional computing infrastructure, most of these projects cannot even be attempted.Broader Impact: This unparalleled simulation resource will be made available to a broader community as well, including students attending summer camps to increase female enrollment in computer science, undergraduates for both educational class project and research use, and researchers in regional departments with insufficient resources to perform high-end simulations.

数字仿真不仅在物理科学的许多领域，而且在计算机科学中也越来越占主导地位。 尽管在过去的几十年里，处理速度有了很大的提高，但对大规模系统的高级研究需要比普通桌面工作站更强大的仿真引擎。德克萨斯大学奥斯汀分校计算机科学系将组装一个基础设施，用于执行大规模、内存密集型的仿真。 这个被称为Mastodon的基础设施将由大量机架式Linux/x86服务器组成，每个服务器都有多个处理器和几千兆字节的物理内存。通过工业和大学的配套资金，我们预计将Mastodon扩展到418个处理器和近1 TB的DRAM。 该集群将使用Condor作业管理软件进行分布式批处理调度，以及用于定时和并行实验的软分区。该基础设施将满足我们部门大多数教师的需求。 使用Mastodon的项目包括系统领域（特别是架构，编译器和运行时系统），网络算法，计算生物学，多智能体机器人和形式验证。 在这些领域中，Mastodon使多个项目变得可行，而在传统的计算基础设施中，这些项目中的大多数甚至无法尝试。这种无与伦比的模拟资源也将提供给更广泛的社区，包括参加夏令营的学生，以增加计算机科学的女性入学率，教育类项目和研究用途的本科生，以及资源不足的地区部门的研究人员进行高端模拟。