Project Summary/Abstract Fred Hutch respectfully requests funds to upgrade the current 523-node, 3328-core high performance computing (HPC) cluster, which was created in 2004 and expanded in 2006, 2010 (S10 funds), 2013, 2015 (S10 funds), and 2018. 456 end of life nodes (1824 cores) will be replaced and 144 nodes (3456 cores) will be added, creating a new 211-node, 4996-core system with an overall 50% increase in core count, 60% increase in processing power, and more than 100% increase in memory capacity over the old system. The expanded capacity will enable deep and efficient analysis of our research studies and accommodate 20% annual growth in computing intensive research, much of which is not possible on the current cluster. The core user group for the new HPC cluster consists of at least 37 NIH-funded research groups participating in this proposal, however as much as 85 groups use the cluster regularly. Their biomedical research is aimed at eradicating cancer and other diseases and dependent on computationally intensive technical approaches such as development of novel statistical analysis or machine learning methods, for example for assessing immune correlates to facilitate vaccine development, analyzing large scale clinical trials or to develop software tools for the analysis of large-scale immunological datasets, DNA and RNA sequencing, modeling prostate cancer outcomes, studies of the human microbiome, modeling of cancers, mRNA, miRNA, and structural variant detection, structural biology with Cryo- EM, modeling of infectious agents and pandemics, computational modeling, prediction and design of macromolecular structures and interactions, identifying drivers of neoplasia and an international consortium improving colorectal cancer detection using GWAS, whole genome sequencing and genome-wide gene- environment (GxE) studies as well as research in diabetes, mhealth and cardiovascular diseases. Several of the Major Users at Fred Hutch are currently experiencing substantial delays in accomplishing their work using the current cluster. Others have projects that cannot be done at all on the existing instrument. (see Research Projects section for details). The Scientific Computing department (SciComp) has operated the current HPC cluster for more than 10 years and has a staff with a combined experience of over 150 years. The proposed new HPC cluster will be installed in available space in a Fred Hutch datacenter. The expanded cluster will address both immediate and future needs of our user community, supporting NIH-funded research at Fred Hutch. Funded research at our Center will greatly benefit from the increased data-processing capacity and improved performance of the requested HPC cluster, including applications of machine learning to the study of clinical trial efficacy, comparison of immune system receptors to identify responses to specific pathogens/diseases, modeling of carcinogenesis. Besides multiple infectious diseases Fred Hutch researches all types of cancer and our computationally intensive investigators tend to focus on colon, prostate, brain, Barrett’s esophagus, lung and liquid tumors such as leukemia.

Project Narrative (Public Health Relevance) We are requesting an expansion of our high-performance computing (HPC) cluster to provide capacity for the growing computational needs in a broad range of biomedical research studies at our Center. Access to fast and reliable computational power is critically important for analyzing the exploding amounts of data produced by large-scale clinical and epidemiological studies, as well as scientific instruments such as genome sequencers and electron microscopes. The prevention, detection, and treatment of cancer, HIV, and other life-threatening diseases are major areas of NIH-funded research at our Center that will greatly benefit from the improved performance of the requested HPC cluster, including large-scale clinical and epidemiologic studies of various cancers, modeling of vaccine efficacy, and infectious disease transmission and proteomic-based biomarker discovery.