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.
A new software model helps move million-line codes to various hardware architectures by automating data movement in unique ways.
Apollo, an auto-tuning extension of RAJA, improves performance portability in adaptive mesh refinement, multi-physics, and hydrodynamics codes via machine learning classifiers.
Cluster Management Tools
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.
PDES focuses on models that can accurately and effectively simulate California’s large-scale electric grid.
Math for Data Mining
Newly developed mathematical techniques reveal important tools for data mining analysis.
GLVis is a lightweight tool for accurate and flexible finite element visualization that provides interactive visualizations of general FE meshes and solutions.
LLNL’s Stack Trace Analysis Tool helps users quickly identify errors in code running on today’s largest machines.
High-Order Finite Volume Methods
High-resolution finite volume methods are being developed for solving problems in complex phase space geometries, motivated by kinetic models of fusion plasmas.
Researchers are developing a standardized and optimized operating system and software for deployment across Linux clusters to enable HPC 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
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.
Derived Field Generation
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.
Researchers are testing and enhancing a neutral particle transport code and its algorithm to ensure that they successfully scale to larger and more complex computing systems.
Data-Intensive Computing Solutions
New platforms are improving big data computing on Livermore’s high performance computers.
HPC Code Performance
LLNL researchers are finding some factors are more important in determining HPC application performance than traditionally thought.
CT Image Enhancement
Researchers are developing enhanced computed tomography image processing methods for explosives identification and other national security applications.
LLNL and University of Utah researchers have developed an advanced, intuitive method for analyzing and visualizing complex data sets.
Testbed Environment for Space Situational Awareness software helps to track satellites and space debris and prevent collisions.
The flourishing of simulation-based scientific discovery has also resulted in the emergence of the UQ discipline, which is essential for validating and verifying computer models.
Spindle improves the library-loading performance of dynamically linked HPC applications by plugging into the system’s dynamic linker and intercepting its file operations.
Caliper enables users to build customized performance measurement and analysis solutions by connecting independent context annotations, measurement services, and data processing services.
Serpentine Wave Propagation
These methods for solving hyperbolic wave propagation problems allow for complex geometries, realistic boundary and interface conditions, and arbitrary heterogeneous material properties.