Computing at LLNL
Browse Projects

At a Glance

Discovery science and technical innovation

Computing at LLNL advances scientific discovery through foundational and innovative research; mission-driven data science; complex modeling, simulation, and analysis on powerful supercomputers; and creative technologies and software solutions. Everything at Livermore is Team Science. Thus, Computing is at the heart of many of LLNL’s most compelling national security and scientific efforts:

  • Operating one of the world’s largest HPC data centers
  • Deploying research and supercomputers to mitigate COVID-19
  • Preparing for one of the nation’s first exascale-class computers
  • Providing essential IT expertise across LLNL
  • Running one of the world’s largest control systems at NIF
  • Advancing cancer research and treatment
  • Designing AI and machine learning algorithms for science-based pattern discovery

Focus Areas

Computational Math

Powering scientific codes with advanced algebraic methods, algorithms, solvers, and discretizations

Computational Science

Supporting the Lab’s mission-driven programs with scientific modeling and simulation

Cyber Security

Meeting the nation’s top priorities to enhance security in a highly interconnected world

Data Science

Advancing AI, data analytics, machine learning, predictive modeling, statistics, UQ, and more

Emerging Architectures

Innovating in new directions for next-generation hardware designs and platform integrations

HPC Systems & Software

Providing environments, tools, and expertise for vital national security research and development

Information Technology

Meeting the Lab’s computer technology needs every day with enterprise applications and services

Software Engineering

Applying best practices to maximize the efficiency of software development and deployment

News

collage of 19 people and the UnifyFS logo


Source: LLNL News

Lab scientists win R&D 100 awards

An optics element team and two open-source software teams (UMap and UnifyFS) are LLNL's winners of this year's awards.

Awards | HPC Systems and Software | Open-Source Software

four people at computer workstations in a dark blue server room


Source: LLNL Computing

Measuring failure risk and resiliency in AI/ML models

A CASC researcher and collaborators study model failure and resilience in a paper accepted to the 2024 International Conference on Machine Learning.

AI/ML | Data Science | Deep Learning | ML Theory | UQ and Statistics

shield icon with a lock icon on an abstract blue background with rays of lines fanning out from the bottom of the shield


Source: LLNL Computing

Measuring attack vulnerability in AI/ML models

LLNL researchers study model robustness in a paper accepted to the 2024 International Conference on Machine Learning.

AI/ML | Data Science | ML Theory

Highlights

Featured Employee
Maya Gokhale

Maya Gokhale

An LLNL Distinguished Member of Technical Staff, Gokhale is considered an expert in her field, and continues to enjoy the fast pace of innovation and change in computing.

Featured Project
FGFS logo

FGFS

Fast Global File Status (FGFS) is an open-source package that provides scalable mechanisms and programming interfaces to retrieve global information of a file.

Featured Event
two people working at a table with a tutorial playing on a laptop screen

HPC Software Tutorials

Learn how to use a modern, open-source HPC software stack! Throughout August, join our free tutorials on how to install and use several projects on AWS EC2 instances. No previous experience is necessary, and everyone is welcome.

Careers

People standing in front of LLNL block letters

We offer a promising future of discovery science and technical innovation

From software developers and applied math researchers to hardware architects and networking experts, computing at LLNL requires a top-flight workforce with a broad skill set. Check out our internship pages or visit LLNL's careers site to see how you can be a part of the future.