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LLNL’s Computing & Communications portfolio is a gateway for accessing LLNL’s wide variety of solutions and intellectual property for use in information technologies, communications, quantum sciences, data sciences and applied software/modeling & simulations. LLNL’s long history and strong capabilities in computing underpin our success in research, in developing new solutions for our missions, and in our collaborations with the academic and private sectors. We license solutions via diverse mechanisms suited to the use cases, ranging from open-source software licensing, to nonexclusive end user licenses, to custom proprietary licenses for distributors, startups, and other commercialization licensees. We also collaborate with industry partners interested in applying LLNL’s unique capabilities and computing solutions to their company’s challenges.

Portfolio News and Multimedia

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An Open-Source, Data-Science Toolkit for Energy Grids

Lawrence Livermore National Laboratory has developed GridDS — an open-source, data-science toolkit for power and data engineers that will provide an integrated energy data storage and augmentation infrastructure, as well as a flexible and comprehensive set of state-of-the-art machine-learning models.

One ID

With business applications moving to the cloud from traditional corporate networks, a crucial part of any organization’s cybersecurity is managing the users who can access their computers, networks, software applications and data. LLNL’s One ID technology is a cost-effective way to more easily manage a large organization’s enterprise security.

Livermore Tomography Tools: Accurate, Fast, and Flexible Software Solution for Data Processing and Reconstruction by Kyle Champley

Join us to hear about the latest in CT image reconstruction and data processing. Medical imaging, industrial manufacturing inspection and airport luggage security rely on CT. LLNL researchers have developed an innovative software product that betters the competition in imaging fidelity.

IT and Communications Technologies

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CT Scanner Adobe Stock Image

The essence of this invention is a method that couples network architecture using neural implicit representations coupled with a novel parametric motion field to perform limited angle 4D-CT reconstruction of deforming scenes.

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AI Innovation Incubator

Lawrence Livermore National Laboratory (LLNL) is offering the opportunity to collaborate in accelerating artificial intelligence (AI) for applied science, including research in key areas such as advanced material design, 3D printing, predictive biology, energy systems, “self-driving” lasers and fusion energy research.

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Plasma wind
CRETIN is a 1D, 2D, and 3D non-local thermodynamic equilibrium (NLTE) atomic kinetics/radiation transport code which follows the time evolution of atomic populations and photon distributions as radiation interacts with a plasma consisting of an arbitrary mix of elements. It can provide detailed spectra for comparing with experimental diagnostics.
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Livermore Tomography Tools  LTT

To solve these challenges using new and existing CT system designs, LLNL has developed an innovative software package for CT data processing and reconstruction. Livermore Tomography Tools (LTT) is a modern integrated software package that includes all aspects of CT modeling, simulation, reconstruction, and analysis algorithms based on the latest research in the field. LTT contains the most…

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Catalyst HPC cluster

Clinical images have a wealth of data that are currently untapped by physicians and machine learning (ML) methods alike. Most ML methods require more data than is available to sufficiently train them. In order to obtain all data contained in a clinical image, it is imperative to be able to utilize multimodal, or various types of, data such as tags or identifications, especially where spatial…

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medical_x-rays_x-ray_tech

Some COVID-19 diagnoses are utilizing computed tomography (CT)-scans for triage. CT-scans produce immediate results with high sensitivity. The digital images produced by a CT-scan require physicians to identify objects within the image to determine the presence of disease. Object identification can be done using machine learning (ML) techniques such as deep learning (DL) to improve speed and…

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MimicGAN data set example

MimicGAN represents a new generation of methods that can “self-correct” for unseen corruptions in the data out in the field. This is particularly useful for systems that need to be deployed autonomously without needing constant intervention such as Automated Driver Assistance Systems. MimicGAN achieves this by treating every test sample as “corrupt” by default. The goal is to determine (a) the…

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Toy model demonstration of a Napier Deltic Engine. Thermo-structural analysis in Diablo with piston pressure. Simrev software-twin is seven python modules; pistons, crank-arms, gears, etc.; and a main program. Total 600 lines of code.

Simrev is a python library imported into a user-generated program. As the program grows in capability and complexity, the engineered product matures. The "software twin" handles all changes to product configuration and is the portal to running supercomputing analysis and managing workflow for engineering simulation codes. Assemblies become program modules; parts, materials, boundary conditions…

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medical_x-rays_x-ray_tech

LLNL has developed a new system, called the Segmentation Ensembles System, that provides a simple and general way to fuse high-level and low-level information and leads to a substantial increase in overall performance of digital image analysis. LLNL researchers have demonstrated the effectiveness of the approach on applications ranging from automatic threat detection for airport security, to…