Advanced Scientific Computing Research Marquee 1920x800 Opt
  1. LANL Home
  2. Science & Engineering
  3. Science Programs
  4. Office of Science Programs

Advanced Scientific Computing Research

ASCR at LANL

Utilizing specialized computer science and applied mathematics to develop supercomputing technologies to solve real world problems today and develop the technology of the future.

The Department of Energy Office of Science's Advanced Scientific Computing Research (ASCR) program supports specialized computer science and mathematics research and development aimed at solving today’s real world high-performance computing challenges and developing the technologies of the future. At LANL we work with ASCR in a number of areas including:

  • Data science, including visualization and analytics
  • Programming models & runtime systems
  • Storage systems
  • Advanced computing technologies (e.g., quantum computing)
  • Fundamental and focused topics across computational sciences

Exascale Computing Projects

LANL has roles in leadership and technical project execution within the DOE’s Exascale Computing Project (ECP). The upcoming era of exascale computing platforms will drive breakthroughs in

  • materials science
  • additive manufacturing
  • chemical design
  • artificial intelligence and machine learning
  • cancer research and treatment
  • earthquake risk assessment

LANL’s project portfolio

  • The Exascale Atomistic capability for Accuracy, Length and Time (EXAALT) application
  • The Co-design Center for Particle Applications (CoPA)
  • The Co-design Center for Machine Learning (ExaLearn)
  • The Legion Programming System

Scientific Discovery Through Advanced Computation (SciDAC) Institutes

  • Resource and Application Productivity through computation, Information, and Data Science (RAPIDS)

SciDAC-4

  • Biological and Environmental Research
    • Coupling Approaches for Next Generation Architectures (CANGA)
    • Actionable Projections of Sea-Level Change from Ice Sheet and Earth System Models (ProSPECT)
    • A New Discrete Element Sea-Ice Model for Earth System Modeling
    • Non-Hydrostatic Dynamics with Multi-Moment Characteristic Discontinuous Galerkin (NH-MMCDG) Methods
    • Development of Terrestrial Dynamical Cores for the ACME to Simulate Water Cycle

Fusion Energy Sciences

  • Tokamak Disruption Simulation
  • Plasma Surface Interactions: Predicting Performance and Impact of Evolving PFC Surfaces
  • Center for High-Fidelity Boundary Simulation (HBPS)

High Energy Physics

  • Accelerating HEP Science: Inference and Machine Learning of Extreme Scales

Nuclear Physics

  • Nuclear Computational Low Energy Initiative (NUCLEI)
  • Computing the Properties of Matter with Leadership Computing Resources
  • Towards Exascale Astrophysics of Mergers and Supernovae (TEAMS)

Nuclear Energy

  • Simulation of Fission Gas in Uranium Oxide Nuclear Fuel

7 Los Alamos researchers named 2024 Laboratory Fellows

Novel Hardware Approach Produces a New Quantum Computing Paradigm

Los Alamos team cracks the code on the bane of quantum machine learning algorithms

Greenland Ice Sheet “Sliding” a Small Contributor to Future Sea-Level Rise

Unveiling the Existence of the Elusive Tetraneutron

Share

Contacts

  • Pat McCormick
  • Email
  • Danny Perez
  • Email
  • Stephan Eidenbenz
  • Email
  • Luis Chacon
  • Email