Lawrence Livermore National Laboratory

Lawrence Livermore National Laboratory


Bronis R de Supinski


Email: bronis@llnl.gov
Phone: 925-422-1062


Bronis R. de Supinski is the Chief Technology Officer (CTO) for Livermore Computing (LC) at Lawrence Livermore National Laboratory (LLNL). In this role, he is responsible for formulating LLNL's large-scale computing strategy and overseeing its implementation. His position requires frequent interaction with high performance computing (HPC) leaders and he oversees several collaborations with the HPC industry as well as academia. He is also the LLNL principal point of contact for the Scientific Discovery through Advanced Computing (SciDAC) program's Institute for Sustained Performance, Energy and Resilience (SUPER), for which he leads the resilience thrust.

Prior to becoming CTO for LC, Bronis led several research projects in LLNL's Center for Applied Scientific Computing (CASC). Most recently, he led the Exascale Computing Technologies (ExaCT) project and co-led the Advanced Simulation and Computing (ASC) program's Application Development Environment and Performance Team (ADEPT). ADEPT is responsible for the development environment, including compilers, tools and run time systems, on LLNL's large-scale systems. ExaCT explored several critical directions related to programming models, algorithms, performance, code correctness and resilience for future large scale systems. He currently continues his interests in these topics, particularly programming models, and serves as the Chair of the OpenMP Language Committee.

Bronis earned his Ph.D. in Computer Science from the University of Virginia in 1998, and he joined CASC in July 1998. His dissertation investigated shared memory coherence based on isotach logical time systems. His research has covered a wide range of topics, including applications of data mining techniques to performance analysis and modeling including performance modeling through non-linear regression techniques (i.e., artificial neural networks and piecewise polynomial regression), investigations into mechanisms and tools to improve memory performance, a variety of optimization techniques and tools for MPI, and several issues with OpenMP, including its memory model and tool support.

Throughout his career, Bronis has won several awards, including the prestigious Gordon Bell Prize in 2005 and 2006, as well as an R&D 100 for his leadership of a team that developed a novel scalable debugging tool. He serves on the program committees of numerous conferences and workshops. He is a member of the ACM and the IEEE Computer Society.