Advanced Computing for Science
The Advanced Computing for Science (ACS) Department seeks to create software and tools to enable scientists to address complex and large-scale computing and data analysis problems beyond what is possible today. ACS engages in partnerships with scientists to understand their computing and data analysis challenges and develop leading-edge solutions that fit the needs of the scientists. Current research areas and projects include troubleshooting to enable petascale science, dealing with data and analysis software for the Large Hadron Collider and Daya Bay, processing astronomical data for WFIRST and BOSS, using experimental data to understand climate change impacts, tools and specifications for ecoinformatics, effective utilization of cloud computing, improved workflow tools for the biology and intelligence communities, improved cybersecurity, and protocols for energy efficiency.
» Visit the ACS site.
CyberInfrastructure Development
Group lead: Deb Agarwal. The CID group performs software engineering and research to enable end-to-end scientific computing and analysis. The CID group's work is incorporated into the ACS department… Read More »
Data Intensive Systems
Group lead: Dan Gunter. The DIS group performs applied Computer Science research to enable data-intensive science. The DIS group's work is incorporated into the ACS department… Read More »
Software Systems for Science
Group lead: Craig Tull. The SSS group performs applied research and software engineering for large collaborative science projects such as ATLAS and Daya Bay. The SSS group's work is incorporated into the ACS department… Read More »
