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.
BLT
BLT software supports HPC software development with built-in CMake macros for external libraries, code health checks, and unit testing.
MacPatch
MacPatch provides LLNL with enterprise system management for desktop and laptop computers running Mac OS X.
CHAI
A new software model helps move million-line codes to various hardware architectures by automating data movement in unique ways.
Apollo
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
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
GLVis is a lightweight tool for accurate and flexible finite element visualization that provides interactive visualizations of general FE meshes and solutions.
TOSS
Researchers are developing a standardized and optimized operating system and software for deployment across Linux clusters to enable HPC at a reduced cost.
STAT
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.
ROSE Compiler
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.
CT Image Enhancement
Researchers are developing enhanced computed tomography image processing methods for explosives identification and other national security applications.
InfiniBand
Livermore Computing staff is enhancing the high-speed InfiniBand data network used in many of its high performance computing and file systems.
Ardra
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.
TESSA
Testbed Environment for Space Situational Awareness software helps to track satellites and space debris and prevent collisions.
Topological Analysis
LLNL and University of Utah researchers have developed an advanced, intuitive method for analyzing and visualizing complex data sets.
PSUADE
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.
PAVE
Performance analysis of parallel scientific codes is difficult. The HAC model allows direct comparison of data across domains with data viz and analysis tools available in other domains.
Spindle
Spindle improves the library-loading performance of dynamically linked HPC applications by plugging into the system’s dynamic linker and intercepting its file operations.
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.
Caliper
Caliper enables users to build customized performance measurement and analysis solutions by connecting independent context annotations, measurement services, and data processing services.
LMAT
This genome sequencing technology helps accelerate the comparison of genetic fragments with reference genomes and improve the accuracy of the results as compared to previous technologies.