Data Intensive Science in the Department of Energy: Case Studies and Future Challenges
James Aherns, Bruce Hendrickson, Gabrielle G. Long, Rob Ross, Dean N. Williams, Stephen D. Miller · Computing in Science & Engineering · 2011
We provide a perspective on the opportunities and needs for data intensive science within the Department of Energy. In particular, we focus on two areas in which DOE s landscape is different from those of other organizations. First, DOE is a leader in the use of high performance computing for modeling and simulation, and these computations generate huge amounts of data to manage and analyze. Second, DOE maintains leading experimental facilities and these also produce prodigious quantities of data. Through three case studies, we explore the necessity of data intensive science. We then extract commonalities from these case studies and use them to detail some of the technical challenges we will need to address to realize this vision.