MRI: Acquisition of a High Performance Computer Cluster Supporting Computational Science Research and Learning

提案编号：CNS 09- 22644 PI：Robila，Stefan A.机构：蒙特克莱尔州立大学标题： MRI/采集：支持计算科学研究和学习的高性能计算机集群项目建议：该项目，获得一个高性能计算机集群，旨在扩大三个部门（计算机科学，数学科学和语言学）的跨学科项目，并与研究密集型大学（锡拉丘兹）合作。这些项目需要强大的计算能力，并描述了数据集大小持续增长的问题。这项工作涉及并行图像和信号处理的新方法，特别是光谱成像。该方法包括并行算法的设计和如何并行化一般数据处理步骤的理论发展。其他项目使用并行处理进行系统发育建模，使用动态系统进行疾病建模，使用散射理论的并行化技术，以及跨语言的形态句法标记。更广泛的影响：该项目有助于吸引更多的学生参与多学科研究，并建立和加强本科教学机构与研究型大学之间的跨机构研究伙伴关系。对光谱成像并行应用的研究允许在新的应用中使用光谱传感器，提高结果的及时性和准确性。在动态系统方面，疾病动态的计算机建模和计算分析可能有助于确定针对特定流行病情况的最佳政策。散射理论在科学上的应用和贡献包括深层地震学、地下资源勘探、工程、地雷探测和其他军事应用。在遗传学中，基于客观标准重建最优进化树的能力直接影响对生物体、人类进化和传染病传播之间关系的理解。

Proposal #: CNS 09-22644PI(s): Robila, Stefan A.Institution: Montclair State University Title: MRI/Acq.: High Performance Computer Cluster Supporting Computational Science Research and LearningProject Proposed:This project, acquiring a high performance computer cluster, aims to expand interdisciplinary projects in three departments (CS, Math Science, and Linguistics) and enable collaboration with a research intensive university (Syracuse). These projects require significant computation power and describe problems where the size of the data sets continues to grow. The work involves novel approaches for parallel image and signal processing, and in particular spectral imaging. The approach includes design of parallel algorithms and the development of theories on how to parallelize the general data processing steps. Other projects use parallel processing for phylogenetic modeling, use dynamic systems for disease modeling, parallelization techniques for the use of scattering theory, and the cross-lingual morphosyntactic tagging.Broader Impacts: This project helps to attract more students to hands-on multidisciplinary research and to establish and strengthen a cross-institutional research partnership between an undergraduate-serving teaching institution and a research university. The research on spectral imaging parallel applications allows for the use of spectral sensors in new applications improving the timeliness and accuracy of results. In terms of dynamic systems, computer modeling and computational analysis of disease dynamics might contribute to determine the best policy for a given epidemic situation. Applications and contributions of scattering theory to science include deep earth seismology, exploration of underground resources, engineering, mine detection, and other military applications. In phylogeny, the ability to reconstruct optimal evolutionary trees based on objective criteria impacts directly the understanding of the relationships among organisms, human evolution, and spread of infectious disease.