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Data-Intensive Computing Solutions
New platforms are improving big data computing on Livermore’s high performance computers.

Topological Analysis
LLNL and University of Utah researchers have developed an advanced, intuitive method for analyzing and visualizing complex data sets.

HZIP
hzip 1.0.1 is a C++ library for lossless compression of structured and unstructured meshes composed of cells with hypercube topology.

Measuring attack vulnerability in AI/ML models
LLNL researchers study model robustness in a paper accepted to the 2024 International Conference on Machine Learning.

LLNL, DOD, NNSA dedicate Rapid Response Laboratory and supercomputing system to accelerate biodefense
The collaboration has enabled expanding systems of the same architecture as LLNL’s upcoming exascale supercomputer, El Capitan, featuring AMD’s cutting-edge MI300A processors.

Evaluating trust and safety of large language models
In two papers from the 2024 International Conference on Machine Learning, Livermore researchers investigate how LLMs perform under measurable scrutiny.