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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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4D Computed Tomography Reconstructions

LLNL’s Distributed Implicit Neural Representation (DINR) is a novel approach to 4D time-space reconstruction of dynamic objects.  DINR is the first technology to enable 4D imaging of dynamic objects at sufficiently high spatial and temporal resolutions that are necessary for real world medical and industrial applications. 

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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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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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Sequoia computer panels off

LLNL has developed a new active memory data reorganization engine. In the simplest case, data can be reorganized within the memory system to present a new view of the data. The new view may be a subset or a rearrangement of the original data. As an example, an array of structures might be more efficiently accessed by a CPU as a structure of arrays. Active memory can assemble an alternative…