Proteins to Population:A metacluster for Bioinformatics

点击翻译按钮获取中文摘要

DESCRIPTION (provided by applicant): This proposal seeks funding to build a "meta-cluster" to enable the new generation of bioinformatics applications under development at the University of Utah. Meta-clustering moves beyond the concept of a single general purpose computational cluster to specifically tailor resources and computational elements towards problems for which they are optimized. These resources will include a computational "cycle farm", a tightly coupled cluster with fast internode communication for optimitized parallel processing, a visualization cluster a tightly coupled data intensive storage/processing unit and two large storage facilities together forming the meta-cluster.Beyond building such a cluster, a key component of the meta-cluster environment is facilitating and managing access to these resources by individual researchers. Using highly advanced scheduling techniques (Maui/Silver) under development at the Center for High Performance Computing (CHPC) at Utah, each of the separate elements will be seamlessly integrated (from a user's perspective) into what appears to be a single resource. Based on our extensive experience in building and operating clusters of commodity hardware, we have designed the meta-cluster to not only provide the necessary resources for our emerging set of applications but done so in the most cost effective manner. The proposed bio-informatic applications exhibit a large degree of variability, have varied computational, visualization, data and parallel processing needs, and therefore require access to quite heterogeneous resources to perform optimally. These applications range from epidemiological studies of populations to investigations of the mechanics of knees or studies of organ level systems down to detailed atomistic simulations of various biomolecular systems.