SCREMS: Scientific Computing Research Environments for the Mathematical Sciences

该奖项将向威斯康星大学麦迪逊分校数学系提供资金，与威斯康星大学Eau Claire大学、怀特沃特大学和麦迪逊地区技术学院(MATC)的数学教师合作，为数学科学的跨学科研究及其在生物和基础医学科学中的应用实施高性能计算环境网络。这个学术网络将与美国领先的工业合作伙伴(太阳网格网络、NVIDIA和PBC线性自动化技术)密切合作，提供一种新的方法，使威斯康星州的学生和教师能够更广泛地参与基于分布式大规模并行GPU的计算的应用，以及麦迪逊研究小组在计算机科学、遗传学和数学方面的应用。项目成果包括：应用拓扑学准确确定大型蛋白质的结构，应用流体动力学中的拓扑学方法，数学建模和计算来确定基因在植物根系发育中的功能。此外，新的算法将使研究人员能够克服目前在可视化和分析超高维海量数据集方面的障碍，这些数据集是21世纪农学、药物发现和系统生物学中生物技术的标志。

This award will provide funds to the Department of Mathematics at University of Wisconsin Madison in collaboration with mathematics faculty at UW Eau Claire, UW Whitewater and the Madison Area Technical College (MATC) to implement a network of high performance computing environment for interdisciplinary research in the mathematical sciences and its applications to biological and basic medical sciences. This academic network will collaborate closely with pioneering American industrial partners (SUN Grid Network.com, nVIDIA and PBC Linear automation technologies) to provide a novel approach that enables a broader participation of students and faculty from the State of Wisconsin in advancing applications of distributed massively parallel GPU-based computation along with the Madison research groups in the computer sciences, genetics and mathematics.The project outcomes include: applications of topology to accurately determine structure of large proteins, topological methods in fluid dynamics, mathematical modeling and computations to determine functions of genes in development of plant root systems. Further, novel algorithms will enable researchers to overcome current obstacles for visualization and analysis of very high dimensional massive data sets that are the hallmarks of the 21st century biotechnology in agronomy, drug discovery, and systems biology.