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
  • Designing AI and machine learning algorithms for science-based pattern discovery
  • Driving advances in simulation, scalable visualization, and data management
  • Providing essential IT expertise across LLNL
  • New simulation technologies and algorithms, such as in design optimization and decision support
  • Computing beyond exascale: heterogeneous, neural, cloud/converged, and quantum
  • Running one of the world’s largest control systems at NIF

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

Adobe Stock illustration of a brain shape made up of teal and pink filaments on an abstract background


Source: LLNL Computing

ICLR25 acceptances

LLNL researchers have posters and workshop papers accepted to the 13th International Conference on Learning Representations on April 24–28.

AI/ML | Data Science | Deep Learning | Events | ML Theory | Natural Language Processing | Scientific ML

General flowchart of the pipeline for building the Centrifuge reference database based on the BLAST nt database


Source: LLNL News

New nucleotide database could improve microbe identification for science and medicine

LLNL researchers have created new, optimized indices of the nt database that simplify how scientists classify microorganisms found in various samples, significantly improving the ability to identify and understand the myriad microorganisms that inhabit our world.

Bioinformatics | Data Management | Data Science | Databases/IT Infrastructure | Information Technology

red and teal antibody structure


Source: LLNL News

LLNL scientists use AI to optimize antibodies against mutations and accelerate pandemic preparedness

Researchers from LLNL, in collaboration with other leading institutions, have successfully used an AI-driven platform to preemptively optimize an antibody to neutralize a broad diversity of SARS-CoV-2 variants.

AI/ML | Biology/Biomedicine | Collaborations | Computational Science | Data Science | Scientific ML

Highlights

Featured Employee
Remesh in front of Sierra

Ramesh Pankajakshan

Computational Scientist Ramesh Pankajakshan came to LLNL in 2016 directly from the University of Tennessee at Chattanooga. But unlike most recent hires from universities, he switched from research professor to professional researcher.

Featured Project
person working at a laptop whose screen is filed with code

Software Development Community

The Software Improvement Networking Group connects developers across LLNL through best practices in software tools, development methodologies, DevOps, security compliance, and more.

Featured Event
Adobe Stock illustration of a brain shape made up of teal and pink filaments on an abstract background

ICLR Acceptances

Congratulations to the Livermore researchers whose work has been accepted to the 13th International Conference on Learning Representations (ICLR) on April 24–28.

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.