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PROJECTS
Performance data mapped onto the material mesh from the LULESH hydrodynamics application
Legacy

Machine Learning

LLNL computer scientists use machine learning to model and characterize the performance and ultimately accelerate the development of adaptive applications.

two CT images

CT Image Enhancement

Researchers are developing enhanced computed tomography image processing methods for explosives identification and other national security applications.

diagram showing data relationships in a particle dataset
Legacy

Data-Intensive Computing Solutions

New platforms are improving big data computing on Livermore’s high performance computers.

NEWS
predictions across different biomolecular complexes by the preview release of OpenFold3

LLNL and partners launch record-breaking protein-folding workflow on world’s fastest supercomputer

Scientists at LLNL and collaborators at AMD and Columbia University have achieved a milestone in biological computing: completing the largest and fastest protein structure prediction workflow ever run, using the full power of El Capitan.

simulation of  a red and blue splash ring on a black background with LLNL and SC25 logos

SC25 event calendar

LLNL is participating in the 37th annual International Conference for High Performance Computing, Networking, Storage, and Analysis (SC25) in St. Louis on November 16–21, 2025.

diagram of interaction between ParaView and Claude

ParaView-MCP levels the playing field for complex scientific visualization

A new study led by CASC researchers empowers users to interact with the application through natural-language and visual inputs instead of the typical graphic user interface, which can appear daunting for novice users.