PNNL

Barker studied computer science at North Carolina State University and the University of Notre Dame before earning his PhD in 2004 from the College of William and Mary in Virginia in the area of runtime software tools to support adaptive and dynamic large-scale parallel scientific applications. He began his career at Los Alamos National Laboratory, where he worked on developing models to describe large-scale scientific application performance on current and future supercomputing architectures. These models were used to drive procurements and guide workload optimizations to enable scientific codes to achieve greater performance, scalability, and efficiency on high-performance computing systems.

Moving to PNNL in 2010, Barker currently leads the Future Computing Technologies group.  He researches advanced computing architectures, AI for autonomous science, and hardware/software co-design methods, primarily supported by the Department of Energy (DOE), Office of Science, Advanced Scientific Computing Research (ASCR) program.  He currently serves as the thrust lead for hardware verification and validation, as well as advanced architecture testbeds, under the ENCODE (End-to-end Co-design for Performance, Energy Efficiency, and Security in AI-enabled Computational Science) project.  Previously, he led the CENATE (Center for Advanced Technology Evaluation) project, which explored the impacts of emerging and novel technologies on the DOE computing mission, and served as Chief Scientist for the laboratory-funded Data-Model Convergence (DMC) Initiative.

• High-Performance Computing
• Computer Architecture
• Performance Modeling and Analysis
• Runtime System Software
• Programming Models

• PhD in Computer Science, College of William and Mary, 2004
• MS in Computer Science, University of Notre Dame, 2001
• BS in Computer Science, North Carolina State University, 1997

• Association of Computing Machinery