Cluster Computing for Mathematical Sciences at Texas A&M University

德克萨斯 A 数学科学集群计算

• 批准号: 0922866
• 负责人: Frank Sottile
• 金额: $ 5.95万
• 依托单位: Texas A&M Research Foundation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2010-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0922866&HistoricalAwards=false
• 关键词: Cluster; Computing; Mathematical; Sciences; Texas

This proposal would provide computer resources to support three research programs in the Mathematical Sciences at Texas A&M University. Bangerth will work on the computational solution of non-linear inverse problems in tomography arising from biomedical imaging. Of particular interest is the optimization of experimental set-up that may involve tuning hundreds to thousands of design parameters. Carroll will work on nutritional epidemiology and genome-wide association studies. While statistical analysis of empirical data is feasible on a simple multicore machine, current methodology requires the performance of statistical methods to be tested on very large ensembles of simulated data. Sottile and Teitler will take advantage of cluster computing to compute local invariants of algebraic varieties, undertake a census of Galois groups of hundreds of thousands of geometric problems, and continue large-scale testing of conjectures in real Schubert calculus. The primary computer resources requested are 16 additional nodes for the 126-node Texas A&M University Brazos Cluster, which is optimized to perform the large number of single node/processor computations this research requires. This Brazos cluster is a high-throughput cluster created in the Summer of 2008, pooling the resources of five stakeholder research groups in four different colleges (Agriculture and Life Sciences, Engineering, Geosciences, and Science) and the Academy for Advanced Telecommunications and Learning Technologies at Texas A&M University. The Principal Investigators will become stakeholders in the Brazos cluster, giving them priority access to the new nodes and enhancing their access to the rest of the cluster.

这项提案将提供计算机资源，支持德克萨斯农工大学数学科学的三个研究项目。邦格思将致力于生物医学成像层析成像中非线性逆问题的计算解决。特别令人感兴趣的是实验设置的优化，这可能涉及到调整数百到数千个设计参数。卡罗尔将从事营养流行病学和全基因组关联研究。虽然经验数据的统计分析在简单的多核机器上是可行的，但当前的方法需要在非常大的模拟数据集合上测试统计方法的性能。Sottile和Teitler将利用集群计算来计算代数簇的局部不变量，承担数十万个几何问题的Galois群的普查，并继续对实Schubert演算中的猜想进行大规模测试。请求的主要计算机资源是为具有126个节点的德州农工大学布拉索斯集群额外提供16个节点，该集群经过优化，可以执行本研究所需的大量单节点/处理器计算。BRAGOS集群是2008年夏天创建的高通量集群，汇集了四所不同学院(农业和生命科学、工程、地球科学和科学)和德克萨斯农工大学高级电信和学习技术学院的五个利益相关者研究小组的资源。首席调查员将成为布拉索斯集群的利益攸关方，使他们能够优先进入新的节点，并加强他们对集群其余部分的准入。