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          * Metabolic Inflammatory Diseases
        * Integrative Omics
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          * Mass Spectrometry-Based Measurement Technologies
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        * Coastal Science
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        * Subsurface Science
        * Terrestrial Aquatics
      * Materials Sciences
        * Materials in Extreme Environments
        * Precision Materials by Design
        * Science of Interfaces
        * Solid Phase Processing
          * Cold Spray
          * Friction Stir Welding & Processing
          * ShAPE
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        * Dark Matter
        * Flavor Physics
        * Fusion Energy Science
        * Neutrino Physics
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          * Tools and Capabilities
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          * Community Values and Ocean Co-Use
          * Wind Systems Integration
          * Wind Data Management
          * Distributed Wind
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          * Environmental Monitoring for Marine Energy
          * Marine Biofouling and Corrosion
          * Marine Energy Resource Characterization
          * Testing for Marine Energy
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          * Environmental Performance of Hydropower
          * Hydropower Cybersecurity and Digitalization
          * Hydropower and the Electric Grid
          * Materials Science for Hydropower
          * Pumped Storage Hydropower
          * Water + Hydropower Planning
        * Grid Integration of Renewable Energy
        * Geothermal Energy
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        * Bioenergy Technologies
          * Algal Biofuels
          * Aviation Biofuels
          * Waste-to-Energy and Products
        * Hydrogen & Fuel Cells
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          * Emission Control
          * Energy-Efficient Mobility Systems
          * Lightweight Materials
          * Vehicle Electrification
          * Vehicle Grid Integration
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        * Contraband Detection
        * Pathogen Science & Detection
        * Explosives Detection
        * Threat-Agnostic Biodefense
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        * Trusted Systems
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        * Global Nuclear & Radiological Security
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        * Grid Resilience and Decarbonization
        * Internet of Things
        * Maritime Security
        * Millimeter Wave
    * Data Science & Computing
      * Artificial Intelligence
      * Graph and Data Analytics
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      * Computational Mathematics & Statistics
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        * Adaptive Autonomous Systems
      * Visual Analytics
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      * Undergraduate Students
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    * All Facilities
      * Atmospheric Radiation Measurement User Facility
      * Electricity Infrastructure Operations Center
      * Energy Sciences Center
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      * Grid Storage Launchpad
      * Institute for Integrated Catalysis
      * Interdiction Technology and Integration Laboratory
      * PNNL Portland Research Center
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BREADCRUMB

 1. Research
 2. Data Science & Computing
 3. High-Performance Computing

HIGH-PERFORMANCE
COMPUTING

MEETING CHALLENGES WITH
NEW COMPUTATIONAL CAPABILITIES

Open

Our computing research is enabled, in part, by the Constance computing cluster.
The system is a workhorse for parallel applications, including those in
molecular dynamics, climate, and fluid flow calculations, or for high-throughput
computing uses such as in high-energy physics or machine learning.

Andrea Starr | Pacific Northwest National Laboratory


Section Menu
 * Artificial Intelligence
 * Graph and Data Analytics
 * Software Engineering
 * Computational Mathematics & Statistics
 * High-Performance Computing
   * Adaptive Autonomous Systems
 * Visual Analytics

 * News & Updates
 * Attend a High-Performance Computing Event
 * Publications
 * Projects
 * Explainer Articles



At Pacific Northwest National Laboratory (PNNL), high-performance computing
(HPC) encompasses multiple research areas and affects both computer science and
a broad array of domain sciences.

PNNL provides science, technologies, and leadership for creating and enabling
new computational capabilities to solve challenges using extreme-scale
simulation, data analytics, and machine learning. We deliver the computer
science, mathematics, computer architecture, and algorithmic advances that
enable integration of extreme-scale modeling and simulation with knowledge
discovery and model inference from petabytes of data.



Our research covers a multitude of areas, including advanced computer
architectures, system software and runtime systems, performance modeling and
analysis, quantum computing, high-performance data analytics, and machine
learning techniques at scale. Our integrated computational tools enable domain
science researchers to analyze, model, simulate, and predict complex phenomena
in areas ranging from molecular, biological, subsurface, and climate sciences to
complex networked systems. For example, the Scalable High-Performance Algorithms
and Data-Structures library—or SHAD—can provide scalability and performance to
support different application domains, including graph processing, machine
learning, and data mining.

We have recognized expertise in the area of evaluation and capability prediction
for both current and emerging large-scale system architectures. The Center for
Advanced Technology Evaluation (CENATE) project evaluates emerging hardware
technologies for use in future systems, exploring both the performance and
security ramifications of novel architectural designs and features. CENATE uses
both small-scale testbeds and predictive performance modeling to explore system
scales that are currently unavailable.

Our researchers also lead efforts to prepare the U.S. Department of Energy for
the upcoming exascale computing era. We are developing software tools such as
the Global Arrays Toolkit, which provides a high-level, easy-to-use programming
model with abstractions suitable for the science domains it targets. We are also
innovating in areas of data-model convergence, charting a new path in
integrating elements of HPC with data analytics to enable new scientific
discoveries and computational capabilities. 


RECENT NEWS

OCTOBER 28, 2024
Feature


COLLABORATION SPEEDS COMPLEX CHEMICAL MODELING

Read

OCTOBER 21, 2024
News Release


CLOUD COMPUTING CAPTURES CHEMISTRY CODE

Read

OCTOBER 16, 2024
Staff Accomplishment


EXPLORING ENERGY EFFICIENCY THROUGH ANALOG COMPUTING

Read

SEE MORE RELATED NEWS


RESEARCH HIGHLIGHTS

SEPTEMBER 18, 2024
Article


A UNIFIED MATHEMATICAL THEORY FOR BARREN PLATEAUS

Read

JUNE 24, 2024
Article


ENABLING NUCLEAR PHYSICS DISCOVERIES WITH QUANTUM COMPUTING

Read

MAY 31, 2024
Article


PNNL PLAYS HOST TO ANNUAL AI WORKSHOP

Read

SEE MORE RELATED HIGHLIGHTS


FACILITIES & CENTERS

Environmental Molecular Sciences Laboratory


RELATED DIVISIONS

Advanced Computing, Mathematics, and Data
AI and Data Analytics Division


RELATED LINKS

What is Graph Analytics?CENATEExascale Computing Project


CONTACT

Kevin J. Barker
Group Leader, High-Performance Computing Group
kevin.barker@pnnl.gov
509-375-6743



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