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. ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Center for Research Resources (NCRR)
Type
Biomedical Research Support Shared Instrumentation Grants (S10)
Project #
1S10RR023043-01
Application #
7125364
Study Section
Special Emphasis Panel (ZRG1-SBIB-Q (50))
Program Officer
Tingle, Marjorie
Project Start
2006-08-01
Project End
2009-07-31
Budget Start
2006-08-01
Budget End
2009-07-31
Support Year
1
Fiscal Year
2006
Total Cost
$1,510,934
Indirect Cost
Name
Massachusetts General Hospital
Department
Type
DUNS #
073130411
City
Boston
State
MA
Country
United States
Zip Code
02199
Tang, Jianbo; Erdener, Sefik Evren; Li, Baoqiang et al. (2018) Shear-induced diffusion of red blood cells measured with dynamic light scattering-optical coherence tomography. J Biophotonics 11:
Setsompop, Kawin; Fan, Qiuyun; Stockmann, Jason et al. (2018) High-resolution in vivo diffusion imaging of the human brain with generalized slice dithered enhanced resolution: Simultaneous multislice (gSlider-SMS). Magn Reson Med 79:141-151
Karahano?lu, Fikret I??k; Baran, Bengi; Nguyen, Quynh Trang Huong et al. (2018) Diffusion-weighted imaging evidence of altered white matter development from late childhood to early adulthood in Autism Spectrum Disorder. Neuroimage Clin 19:840-847
Kline, Emily; Hendel, Victoria; Friedman-Yakoobian, Michelle et al. (2018) A comparison of neurocognition and functioning in first episode psychosis populations: do research samples reflect the real world? Soc Psychiatry Psychiatr Epidemiol :
Sitnikova, Tatiana A; Hughes, Jeremy W; Ahlfors, Seppo P et al. (2018) Short timescale abnormalities in the states of spontaneous synchrony in the functional neural networks in Alzheimer's disease. Neuroimage Clin 20:128-152
Racine, Annie M; Brickhouse, Michael; Wolk, David A et al. (2018) The personalized Alzheimer's disease cortical thickness index predicts likely pathology and clinical progression in mild cognitive impairment. Alzheimers Dement (Amst) 10:301-310
Wu, Jianxiao; Ngo, Gia H; Greve, Douglas et al. (2018) Accurate nonlinear mapping between MNI volumetric and FreeSurfer surface coordinate systems. Hum Brain Mapp :
Kline, Emily R; Seidman, Larry J; Cornblatt, Barbara A et al. (2018) Depression and clinical high-risk states: Baseline presentation of depressed vs. non-depressed participants in the NAPLS-2 cohort. Schizophr Res 192:357-363
Lee, Jeungchan; Mawla, Ishtiaq; Kim, Jieun et al. (2018) Machine learning-based prediction of clinical pain using multimodal neuroimaging and autonomic metrics. Pain :
Buckley, Rachel F; Mormino, Elizabeth C; Amariglio, Rebecca E et al. (2018) Sex, amyloid, and APOE ?4 and risk of cognitive decline in preclinical Alzheimer's disease: Findings from three well-characterized cohorts. Alzheimers Dement 14:1193-1203

Showing the most recent 10 out of 213 publications