? Advances in computer hardware and software have dramatically improved the compute capabilities available to researchers allowing them to tackle problems such as decoding the human genome that seemed insurmountable even a decade ago. Beowulf clusters, which are multi-computer systems that can be used for parallel computations, have played a significant role in the compute revolution due to their performance / price ratio being 3 to 10 times that of traditional supercomputers. The goal of this proposal is to obtain a Beowulf cluster to relieve the computing bottleneck restricting the investigations of the NIH funded researchers at the University of Massachusetts Medical School. The cluster that will form the nucleus of a CORE facility available to all NIH funded investigators at the medical school, and investigators seeking preliminary results for NIH submissions. There are a number of ways documented in this proposal in which the availability of the computational power of the proposed cluster would advance the science of the individual projects of this proposal. They vary from enabling investigators to use new data collection technologies and experimental approaches which have immense computation requirements to using the tightly coupled nodes of the system to perform calculations, which could not realistically be performed on a single processor. The computing power of the cluster would also allow investigators to reduce the approximations and compromises they made in the design of their proposed investigations that were necessitated by the limited computational resources available to them. The need for the cluster will only increase in the future as new investigators in the areas of bio-informatics, structural biology, molecular biophysics, and imaging are recruited to the university. Finally, the CORE facility will also provide the opportunity for investigators from diverse disciplines to interact, and share computational algorithms and approaches. ? ?
O'Connor, J Michael; Das, Mini; Dider, Clay S et al. (2013) Generation of voxelized breast phantoms from surgical mastectomy specimens. Med Phys 40:041915 |
Glick, Stephen J (2007) Breast CT. Annu Rev Biomed Eng 9:501-26 |
Glick, Stephen J; Thacker, Samta; Gong, Xing et al. (2007) Evaluating the impact of X-ray spectral shape on image quality in flat-panel CT breast imaging. Med Phys 34:5-24 |
Gong, Xing; Glick, Stephen J; Liu, Bob et al. (2006) A computer simulation study comparing lesion detection accuracy with digital mammography, breast tomosynthesis, and cone-beam CT breast imaging. Med Phys 33:1041-52 |