Our research projects vary in size, scope, and duration, but they share a focus on developing tools and methods that help LLNL deliver on its missions to the nation and, more broadly, advance the state of the art in scientific HPC. Projects are organized here in three ways: Active projects are those currently funded and regularly updated. Legacy projects are no longer actively developed. The A-Z option sorts all projects alphabetically, both active and legacy.
Apollo, an auto-tuning extension of RAJA, improves performance portability in adaptive mesh refinement, multi-physics, and hydrodynamics codes via machine learning classifiers.
Large Linux data centers require flexible system management. At Livermore Computing, we are committed to supporting our Linux ecosystem at the high end of commodity computing.
The Enabling Technologies for High-Order Simulations (ETHOS) project performs research of fundamental mathematical technologies for next-generation high-order simulations algorithms.
LibRom is a library designed to facilitate Proper Orthogonal Decomposition (POD) based Reduced Order Modeling (ROM).
Newly developed mathematical techniques reveal important tools for data mining analysis.
PDES focuses on models that can accurately and effectively simulate California’s large-scale electric grid.
Livermore builds an open-source community around its award-winning HPC package manager.
LLNL’s Stack Trace Analysis Tool helps users quickly identify errors in code running on today’s largest machines.
High-resolution finite volume methods are being developed for solving problems in complex phase space geometries, motivated by kinetic models of fusion plasmas.
Researchers have been developing a standardized and optimized operating system and software for deployment across a series of Linux clusters to enable high performance computing at a reduced cost…
ROSE, an open-source project maintained by Livermore researchers, provides easy access to complex, automated compiler technology and assistance.
Master Block List is a service and data aggregation tool that aids Department of Energy facilities in creating filters and blocks to prevent cyber attacks.
A Livermore-developed programming approach helps software to run on different platforms without major disruption to the source code.
Livermore researchers have developed a toolset for solving data center bottlenecks.
LLNL researchers are testing and enhancing a neutral particle transport code and the algorithm on which the code relies to ensure that they successfully scale to larger and more complex computing…
The Earth System Grid Federation is a web-based tool set that powers most global climate change research.
New platforms are improving big data computing on Livermore’s high performance computers.
LLNL researchers are finding some factors are more important in determining HPC application performance than traditionally thought.
Researchers are developing enhanced computed tomography image processing methods for explosives identification and other national security applications.
Livermore computer scientists have helped create a flexible framework that aids programmers in creating source code that can be used effectively on multiple hardware architectures.
LLNL computer scientists use machine learning to model and characterize the performance and ultimately accelerate the development of adaptive applications.
Livermore Computing staff is enhancing the high-speed InfiniBand data network used in many of its high performance computing and file systems.