HPC for Quantitative and Computational Neuroscience

描述（由申请人提供）：本提案要求为普林斯顿神经科学研究所（PNI）提供一个新的高性能计算（HPC）系统。这是为了满足不断增长的用户基础以及前沿神经科学研究中快速增长的数据分析和存储需求。PNI的使命是支持关于心理功能（如感知、注意、记忆、学习、决策和认知控制）背后的神经机制的多学科研究。PNI非常重视正式严谨理论的发展，以及对神经科学数据进行定量分析的复杂方法。他们的工作使用了最先进的方法来记录各级分析的神经活动，从非神经元的单单元和多单元记录

DESCRIPTION (provided by applicant): This proposal requests a new high-performance computing (HPC) system for the Princeton Neuroscience Institute (PNI). This is needed to meet both the growing user base and the rapid growth in data analysis and storage demands of leading edge neuroscientific research. The PNI's mission is to support multidisciplinary research on the neural mechanisms underlying mental functions such as perception, attention, memory, learning, decision making, and cognitive control. PNI places a strong emphasis on the development of formally rigorous theory, and quantitatively sophisticated approaches to the analysis of neuroscientific data. Their work makes use of state-of-the-art methods for recording neural activity at all levels of analysis, from single- and multi-unit recordings of neurons in non human species to whole brain fMRI and EEG studies in humans. The size of the data sets generated by these methods has grown explosively over the last decade, and the methods needed to analyze them have become increasingly computationally demanding. At the same time, the PNI user base has grown and will continue to grow substantially over the next several years, from 15 at its inception in 2005, to 21 at present, and to an expected 26 as it occupies its new building presently under construction (and due for occupancy in 2013). These factors have conspired to place severe strains on existing PNI computing facilities, the limits of which are now constraining the research efforts of its investigators. To meet these needs, this proposal requests support for a new HPC system comprised of a 52 node cluster (with 832 cores) and a 540 TB storage system. This new system will be housed in Princeton University's newly constructed High Performance Computing Research Center (HPCRC), co-administered with the Princeton Institute for Computational Science and Engineering (PICSciE), and linked to other powerful computing systems at the HPCRC by way of a high performance GPFS storage grid. This will allow PNI investigators to leverage the availability of considerable additional CPU power at the HPCRC with transparent access to their data, as well as the expertise of PICSciE staff in parallel computing. Work supported by the PNI aims to deepen our understanding of the neural mechanisms underlying mental functions that are disturbed in a wide range of clinical conditions, including depression, anxiety disorders, schizophrenia, neurological impairments, aging, and drug addiction. PNI investigators are supported, in this work, by grants from a number of NIH institutes, including NIMH, NINDS, NIDA, NIA and NEI. Progress in this work promises to lead to more sophisticated and more effective approaches to the diagnosis, treatment and ultimately cure of mental disease. The current proposal will support the research efforts of PNI investigators by providing them with the technological infrastructure necessary to pursue more sophisticated neuroscientific studies, to conduct more detailed analyses of the data they generate, and to construct more realistic models of neural function used to interpret these findings.