LLNL supports the nation’s security by providing solutions to pressing scientific and engineering challenges with its leading supercomputing expertise and resources. The computational capabilities present in today’s top supercomputers will be available for industrial application by the end of this decade, yet availability of highly scalable commercial codes and their integration into existing business workflows present barriers to adoption for the American private sector. Scaling existing scientific and engineering codes to run on next-generation platforms can reduce these barriers and enable software vendors and their customers to take advantage of high performance computing (HPC).


LLNL offers opportunities for joint software development to bridge the gap between the capabilities of Independent Software Vendors (ISVs) of scientific and engineering application codes and HPC users’ needs. Successful relations will yield a greater number of commercial codes available to run on HPC platforms, software with expanded features and improved performance, and wider availability and usability of existing HPC codes.

Software vendor engagements with LLNL may address such solutions as:

  • Scaling vendor codes to run on HPC platforms
  • Expanding vendor software capabilities with additional solver libraries and tool suites
  • Increasing research discovery through algorithm development and multi-physics integration
  • Optimizing code packages through performance and error analyses
  • Developing easy-to-use interfaces for LLNL’s existing HPC codes
  • Coupling codes, potentially including codes owned by LLNL, for extended compatibility and capability
  • Producing reduced capability software packages for lighter use needs
  • Refining workflows for better business process integration

Lawrence Livermore National Laboratory provides access to the newest advanced hardware platforms and large-scale computing clusters for software development, testing and validation. LLNL also offers expertise in a wide range of computational sciences, algorithm development, large-scale optimization, error analyses, visualization and data analysis.