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HPC Environments

HPC Environments

The High Performance Computing Environments group provides direct customer support and interaction at any technical depth of HPC production systems within HPC Division, the Laboratory, and the NNSA complex. HPC Environments designs, manages and maintains the software environment for customer computing.

The group is also responsible for providing input and support to DOE HPC applications ensuring readiness on current and future HPC systems using performance analysis and profiling tools.

TEAMS

Programming & Runtime Environments Team

Application Readiness (AR) Team

The Application Readiness (AR) team is engaged in a range of tasks to facilitate productive use of current and future HPC platforms by the ASC code teams and others. These includes assisting code teams in porting their development work flows and in optimizing their applications for new systems. AR team members also engages with vendors to improve the efficiency of DOE HPC applications on future systems.

Consulting Team

WLM Team

Our Science/Capabilities

  • User Support — Supporting 2000+ local and offsite users, across various applications, programming languages, compilers, workflows and I/O models
  • Next Generation Readiness
  • Systems and Infrastructure Testing

Resources

Pavilion is a software framework for running and analyzing jobs/tests targeting HPC systems.

  • Pavilion on GitHub

Computing News

All News
2025-09-08Computing

Quantum computers tackle a century‑old math puzzle

A Los Alamos scientist has shown that quantum algorithms can be used to factor group representations — a problem central to particle physics and many other fields — that was thought to be infeasible for computers at any practical scale

2025-08-28Computing

Los Alamos National Laboratory launches frontier AI models on the Venado supercomputer

The Venado supercomputer is now running the latest OpenAI reasoning models on its NVIDIA Grace Hopper GPUs to accelerate national security-related science

2025-07-24Computing

Los Alamos team finds a new path toward quantum machine learning

Gaussian had until now escaped use in the quantum computing realm