MRI: Acquisition of Instrumentation for Coupled Experimental-Computational Neuroscience and Biology Research

建议#：CNS 08-21622PI(S)：Fortes，Jose A.McIntyre，Lauren M.；Moroz，Leonid L.；普林斯，Jose C.；Sanchez，Justin C.机构：佛罗里达大学盖恩斯维尔大学，FL 32611-2002标题：磁共振成像/Acq.：耦合实验-计算神经科学和生物学研究的仪器建议：该项目，获得一个具有共享存储子系统和存储能力的虚拟多计算机仪器，旨在将该仪器用作共享仪器，其资源可以根据需要进行虚拟、预留和配置，用于与神经科学、计算生物学和网络基础设施相关的不同研究活动。它的配置也可以专用并紧密耦合到活体实验，使用与用于实验的现场仪器的网络连接。它可以同时支持多个研究活动，因为它具有支持实时计算机在环实验的独特能力，它能够运行多个并发计算线程，它的共享内存和存储子系统，以及它使用虚拟化技术来管理多个计算环境的共存。为了开发和验证多用户虚拟计算系统的自主计算节点和技术，该仪器提供了性能跟踪和其他所需的监控数据。在脑机接口、神经发生学、基因组学、生物信息学、信号处理、网络基础设施、自主计算和其他领域的研究活动包括：-脑机接口，其中运动控制的皮质模型被动态学习并实时应用，-通过对大量遗传数据和数千种化合物的实时分析进行实验性药物发现，-分析随着神经元的生长、学习和记忆而实时捕获的兆兆字节的遗传数据，以及-使用具有随时间增加的在线计算要求的动态过滤拓扑的在线学习算法。这些活动具有变革性的目标，包括引入实时，并将高性能计算解决到其行为由感测数据的复杂处理驱动的闭环实验和/或系统中。另一个目标涉及提供离线计算能力，以匹配大规模并行DNA测序技术产生的前所未有的速度和数量的遗传数据。

Proposal #: CNS 08-21622PI(s): Fortes, Jose A. McIntyre, Lauren M.; Moroz, Leonid L.; Principe, Jose C.; Sanchez, Justin C.Institution: University of Florida Gainesville, FL 32611-2002Title: MRI/Acq.: Instrumentation for Coupled Experimental-Computational Neuroscience and Biology ResearchProject Proposed:This project, acquiring a virtualized multicomputer instrument with shared-memory subsystems and storage capacity, intends to use this instrument as a shared instrument whose resources can be virtualized, reserved, and configured on demand for different research activities related to neuroscience, computational biology, and cyberinfrastructure. Its configurations can also be dedicated and tightly coupled to in vivo experiments using network connections to in situ instrumentation used for experiments. It can simultaneously support multiple research activities because of its unique capability to support real-time computer-in-the-loop experiments, its ability to run many concurrent computation threads, its shared memory and storage subsystems, and its use of virtualization technology to manage the coexistence of multiple computing environments. To develop and validate autonomic computing nodes and techniques for multiuser virtualized computational systems, the instrument provides traces of performance and other needed monitored data. Research activities in brain-machine interfaces, neurogenesis, genomics, bioinformatics, signal processing, cyberinfrastructure, autonomic computing and other areas include:- Brain-machine interfaces where cortex models for motor control are dynamically learned and applied in real-time,- Experimental drug discovery through real-time analysis of large amounts of genetic data and many thousands of compounds,- Analysis of Terabytes of genetic data captured in real-time as a neuron grows, learns, and remembers, and- Online learning algorithms using dynamic filter topologies with online computation requirements that increase over time.The activities have transformative goals, including the introduction of real-time, and address the high performance computation into closed-loop experiments and/or systems whose behavior is driven by complex processing of sensed data. Another goal involves providing off-line computing capabilities to match the unprecedented rate and volume of genetic data produced by massively parallel DNA sequencing technology.