SILICON GRAPHICS PRISM EXTREME 128P/1TB

该子项目是利用由NIH/NCRR资助的共享仪器赠款提供的资源的许多研究子项目之一。子项目和研究者（PI）可能从另一个NIH来源获得了主要资金，因此可以在其他CRISP条目中表示。列出的机构是用于资助的，不一定是研究者的机构。描述（由申请人提供）：该提案要求资源为一组使用成像研究各种疾病的研究人员创建高性能计算资源。磁共振成像（MR！）已经成为研究大脑功能，生理学和解剖学的重要工具，并且越来越详细。对成像数据的分析现在提出了一系列极具挑战性的新问题，如果用所要求的资源加以适当处理，可以大大改善调查人员的资助研究。这些问题的细节因研究者而异，但有一个共同的功能：需要一个单一的、大的、扁平的地址空间，内存大小为1 TB，可由多个CPU寻址。许多研究者将特别受益于设备计算新的极高通道数MRI系统（如1.5特斯拉和3特斯拉及以上的32和96通道MRI扫描仪）生成的数据的能力。因此，我们建议获得一个高速缓存一致性非均匀内存访问（ccNUMA）的高性能计算机与128个安腾2处理器和1 TB的RAM。目前最接近这些研究人员的设备具有可用RAM量的1/64，因此该设备代表了克服特定计算限制并显着加快许多研究人员资助的生物医学研究的独特机会。

This subproject is one of many research subprojects utilizing the resources provided by a Shared Instrumentation Grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the grant, which is not necessarily the institution for the investigator. DESCRIPTION (provided by applicant): This proposal requests resources to create a high performance computing resource for a group of investigators using imaging to study a variety of diseases. Magnetic resonance imaging (MR!) has become a heavily used tool for studying brain function, physiology, and anatomy at increasingly high levels of detail. Analyses of imaging data now present a new set of extremely challenging problems that, if appropriately addressed with the requested resource, could substantially improve the funded research of the investigators. The specifics of the problems vary by investigator but share a common feature: the need for a single, large, flat address space in memory of 1 terabyte in size, addressable by multiple CPUs. Many investigators would benefit specifically from the ability of a device to compute the data being generated by new very-high- channel-count MRI systems such as 32 and 96 channel MRI scanners at 1.5 Tesla and 3 Tesla and beyond. Therefore, we propose acquiring a cache coherent non uniform memory access (ccNUMA) based high performance computer with 128 Itanium 2 processors and 1 TB of RAM. The closest device currently available to these investigators has 1/64th the amount of RAM available, and therefore this device represents a unique opportunity to overcome the specific computational constraints and significantly speed many investigators funded biomedical research.