Supercomputing: Rutgers' Catalyst for Discovery at the Frontiers of Medicine

描述：新泽西州医学和牙科大学（UMDNJ）和罗格斯大学根据州立法机构的一项法案合并，于2013年7月1日生效。新扩建的罗格斯大学将UMDNJ的医学和牙科专家整合为世界一流的生物医学研究机构。我们在医学、生物学、遗传学、化学、数学、药理学、生物化学、化学和生物化学工程、分子生物学和产科等部门的研究人员都参与了资金充足的研究项目，这些项目需要大量的计算资源。这些研究人员总共有64项美国国立卫生研究院资助的赠款，每年的直接费用总额为6000万美元。许多研究人员都在努力在有限的计算资源上进行计算，而这些资源目前是我们可以使用的。其他研究人员无法充分发挥他们研究的潜力

DESCRIPTION: The University of Medicine and Dentistry of New Jersey (UMDNJ) and Rutgers University were joined by an act of the State Legislature, effective July 1, 2013. This newly enlarged Rutgers University integrates the medical and dental specialists from UMDNJ into a world-class biomedical research institution. Our researchers across the departments of Medicine, Biology, Genetics, Chemistry, Math, Pharmacology, Biochemistry, Chemical and Biochemical Engineering, Molecular Biology and Obstetrics are involved in well-funded research projects that have a need for a large computational resource. In total, these researchers have 64 NIH-funded grants with total annual direct costs of > $60M. Many of the investigators are struggling to perform their calculations on the limited computational resources that are currently at our disposal. Other researchers are not able to realize the full potential of their research due to the lack of sufficient computation. For example, some molecular dynamics simulations will produce more realistic results if the system could be modeled for intervals of up to 1 microsecond, but the limit with our current infrastructure is tens of nanoseconds per month for most systems. As another example, genomics researchers have hundreds of exomes and RNA-seq samples that need to be processed and analyzed, but the research is moving at a slow pace due to the bottle-neck of the analysis pipeline. We are proposing a cluster with 2,800 computational cores, 128GB of RAM per compute node and 465TB of storage in a state-of- the-art, energy efficient, cluster configuration. The use, also, of very fast node interconnects (FDR Infiniband) provides the appropriate fabric for problems that are highly scalable, such as molecular dynamics and docking while at the same time supporting the execution of thousands of individual serial jobs. The new computational cluster will enhance the research of our investigators, taking it to levels unattainable with existing resources. This computational cluster will set a new paradigm for a large-scale, centrally managed resource supporting a broad spectrum of biomedical research.