The goal of LLNL's computational systems and software environment for the ASC Program is to build integrated, balanced, and scalable computational capabilities to meet the predictive simulation requirements of the National Nuclear Security Administration (NNSA). LLNL strives to provide users of ASC computing resources a stable and seamless computing environment for all ASC-deployed platforms. Along with the powerful systems that ASC maintains and continues to field, the supporting software infrastructure that LLNL is responsible for deploying on these platforms includes many critical components, from system software and tools, to input/output (I/O), storage and networking, to post-processing visualization and data analysis tools. Achieving this deployment objective requires sustained investment in applied R&D activities to create technologies that address ASC's unique mission-driven needs for scalability, parallelism, performance, and reliability.

Areas include:

  • Commodity Technology (CT) Systems: Commodity clusters such as Quartz leverage industry advances and open source software standards to build, field, and integrate Linux clusters of various sizes into production service. Catalyst provides a large-scale proving ground for high performance computing technologies.
  • Advanced Technology (AT) Systems: Supercomputers such as El Capitan and Sierra provide advanced, cost-effective architectures designed to achieve extreme speeds in addressing specific, stockpile-relevant issues through development of enhanced performance codes especially suited to run on the systems.
  • Next-Generation Computing Technologies: Includes FastForward and DesignForward that will prepare the ASC applications and computing environment for the next computing paradigm shift to extreme parallelism, via heterogeneous and/or multi-core nodes.
  • System Software and Tools: The system software infrastructure, including the supporting operating system environments and the integrated tools, to enable the development, optimization, and efficient execution of application codes.
  • Input/Output, Storage Systems, and Networking: I/O (data transfer) storage infrastructure in balance with all platforms and consistent with integrated system architecture plans.
  • Post-Processing Environments: Integrated support for end-user visualization, data analysis, and data management.