Computing at LLNL
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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


Recent Tweet

Ignacio Laguna and colleagues standing with the ISC 2023 Hans Meuer Award certificate.

Source: LLNL Computing

Best paper winner finds the sources of calculation inconsistencies

Updating a compiler can affect how code runs, leading to inconsistencies in outputs and creating problems for scientists. A new tool automatically finds the sources of these inconsistencies.

Awards | Compiler Technology | HPC Systems and Software | Open-Source Software

Brian and Bronis in front of the SambaNova hardware

Source: LLNL News

LLNL and SambaNova Systems announce additional AI hardware to support Lab’s cognitive simulation efforts

The addition of the spatial data flow accelerator into LLNL’s Livermore Computing Center is part of an effort to upgrade the Lab’s cognitive simulation (CogSim) program.

Co-Design | CogSim/AI/ML Hardware | Data Science | Emerging Architectures | HPC Systems and Software | Scientific ML

LLNL's supercomputing building

Source: Elastic

National lab uses Elastic to optimize performance of projected world's fastest supercomputer

The Lab was already using Elastic components to gather data from its HPC clusters, then investigated whether Elasticsearch and Kibana could be applied to all scanning and logging activities across the board.

Emerging Architectures | HPC Architectures | HPC Systems and Software | Hybrid/Heterogeneous | Information Technology | Software Engineering


Featured Employee
Brian Van Essen and Bronis de Supinski in front of SambaNova systems

Bronis de Supinski

As CTO of Livermore Computing, de Supinski is responsible for formulating, overseeing, and implementing LLNL’s large-scale computing strategy, requiring managing multiple collaborations with the…

Featured Project
zfp velocity field that looks like blue and orange bubbles in varying degrees of granularity


zfp is an open-source C/C++ library for compressed floating-point and integer arrays that support high throughput read and write random access.

Featured Event
CEED logo on a salmon-colored background


As part of the Exascale Computing Project, the LLNL-led Center for Efficient Exascale Discretizations will hold its seventh and final annual meeting on August 1–3 in a hybrid format. Everyone with interest in the ECP, CEED, hardware and software co-design, and PDE discretization algorithms is welcome to attend.


Team stands in front of HPC

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.