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.
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