Highlights include the HYPRE library, recent data science efforts, the IDEALS project, and the latest on the Exascale Computing Project.
Topic: Exascale
ROSE, an open-source project maintained by Livermore researchers, provides easy access to complex, automated compiler technology and assistance.
LLNL computer scientists use machine learning to model and characterize the performance and ultimately accelerate the development of adaptive applications.
Application-level resilience is emerging as an alternative to traditional fault tolerance approaches because it provides fault tolerance at a lower cost than traditional approaches.
BLAST is a high-order finite element hydrodynamics research code that improves the accuracy of simulations and provides a path to extreme parallel computing and exascale architectures.