High Performance Computing

Our scientists are involved in a broad range of research in the area of High Performance Computing. This research includes:

  • Technologies for future exascale computing (more)
  • New programming models for parallel multicore and grid/cloud computing (more)
  • Design and implementation of declarative methods for scalable parallel programming, including those targeting many-cores, GPUs, and large clusters (more)
  • Bioinformatics, Defense, Earthquake and Ice-sheet Science, Particle Physics and Chemical Informatics (more)
  • Open Message Passing Interface (OMPI), LAM (Local Area Multicomputer) implementation of MPI, Boost Graph Library, Parallel Boost Graph Library, Interative Template Library, Matrix Template Library (more)
  • Data-intensive computing at the intersection of Cloud and multicore technologies, life science applications using MapReduce and traditional parallel and distributed computing approaches (more)
  • Software component systems for scientific computing, in particular the XCAT, Indiana University’s distributed computing implementation of the Common Component Architecture specification (more)
  • Compiler techniques to eliminate performance bottlenecks in high-level programming languages, such as MATLAB and R 

Faculty in this area include:
Matthew Anderson, Ariful Azad, Randall Bramley, Volker Brendel, Arun Chauhan, Geoffrey Fox, Vikram Jadhao, Lei Jiang, Andrew Lumsdaine, Judy Qiu, Jeremy Siek, Thomas Sterling, Martin Swany, Clint Whaley