Computing & Computational Sciences

We are home to the nation’s most powerful supercomputer and a premier source for applied mathematics, quantum information science, artificial intelligence research, and data sciences R&D, including the modeling, simulation, and analysis of rapidly growing data sources.

About the Computing & Computational
Sciences Directorate

The Computing and Computational Sciences Directorate (CCSD) oversees ORNL’s immense store of computing power and its talented staff of computational scientists and mathematicians, conducting state-of-the-art research and development in support of DOE’s missions and programs.

The directorate stewards the Oak Ridge Leadership Computing Facility (OLCF), home to the nation’s most powerful supercomputer, Summit, which enables us to address, with greater complexity and higher fidelity, questions concerning who we are, as well as our place on earth and in our universe. The OLCF will also be home to Frontier, ORNL’s upcoming exascale supercomputer scheduled for delivery in 2021.

CCSD contains the institutional knowledge needed to transform basic science into cutting-edge energy and security applications critical to national interests. Our organization is committed to research and development in the data sciences, including the modeling, simulation, and analysis of rapidly growing data sources. The directorate is also a premier source for high-performance computing, applied mathematics, quantum information science, and artificial intelligence research.

BREAKTHROUGH SCIENCE AT EVERY SCALE

Researchers from around the world use the Oak Ridge Leadership Computing Facility to solve problems so challenging they require the world’s most powerful computers. OLCF’s high- performance computing systems—supercomputers—coupled with the expertise of our scientific and technical staff help solve challenges in diverse fields. These challenges include improving the safety and performance of nuclear power plants, designing new materials that can revolutionize industries, and modeling the origins of the universe.

The research portfolio for Computing and Computational Sciences spans three research divisions to advance key science, technology and engineering abilities while building a competitive, world-class workforce to meet our future mission needs.

The Computer Science and Mathematics Division delivers fundamental and applied research capabilities in a wide range of areas, including applied mathematics and computer science, experimental computing systems, scalable algorithms and systems, artificial intelligence and machine learning, data management, workflow systems, analysis and visualization technologies, programming systems and environments, and system science and engineering.

The Computational Sciences and Engineering Division focuses on trans disciplinary computational science and analytics at scale to enable scientific discovery across the physical sciences, engineered systems, and biomedicine and health. It provides foundations and advances in quantum information sciences to enable quantum computers, devices, and networked systems. It also develops community applications, data assets, and technologies and provides assurance to build knowledge and impact in novel, crosscut science outcomes.

The National Center for Computational Sciences provides state- of-the-art computational and data science infrastructure, coupled with dedicated technical and scientific professionals, to accelerate scientific discovery and engineering advances across a broad range of disciplines. NCCS hosts the Oak Ridge Leadership Computing Facility, one of DOE’s National User Facilities.

Pioneers of Leadership Computing

We advance scientific knowledge through modeling and simulation on powerful supercomputers, the development and application of advanced data-intensive science analytics, and foundational investments in applied mathematics and computer science. Our strategy intentionally converges the four paradigms of scientific discovery: theory, experiment, data, and simulation. Over the past decade we have deployed three of the world’s most powerful supercomputers, all ranked fastest in the world at the time of deployment. The installation of the Frontier supercomputer system will be the next step in fielding unsurpassed computational capabilities. Through the accompanying foundational research in Mathematics and Computer Science, coupled with domain science expertise, we will create applications that fully utilize our unique computational infrastructure, enabling scientific discoveries previously thought impossible.

TEN-YEAR VISION
Over the next decade we will be evolving our approach to move from a system-level to an ecosystem-level— where we will maximize the convergence of theory, experiment, data and simulation. We will accelerate innovation for science and technology through advanced computing, including: mission driven advances in computer science, mathematics and computational science; AI and data science from foundations to applications; developing community applications, data assets, and technologies; and foundations and advances in quantum information sciences. Our vision of the Lab of the Future includes the R&D necessary to deploy the use of computing at the edge, federated instruments, autonomy and the Internet of Things (IOT). Over the next decade, we will lead transformational science and technology to enable the flexible, secure, and autonomous energy systems of the future. We will provide power and fuel originating from a variety of sources in a clean and seamless manner.

Computing and Computational Sciences Divisions, Sections and Groups

Computational Sciences and Engineering Division

The Computational Sciences and Engineering Division focuses on trans disciplinary computational science and analytics at scale to enable scientific discovery across the physical sciences, engineered systems, and biomedicine and health sciences. It provides foundations and advances in quantum computation and information science and develops community applications, data assets, and technologies to advance crosscutting science outcomes.

Advanced Computing Methods for Physical Sciences Section

Delivers multiscale, multifidelity computational models and systems developing algorithms and analytics for the physical sciences.

  1. Computational Earth Sciences Group —Develops extreme-scale models and data analytics methods applied to Earth systems modeling. Examples include E3SM and ILAMB, among others.
  2. Computational Chemistry and Nanomaterials Group —Delivers nanomaterials and chemical science at the forefront of the field through HPC. Leads and contributes to the development of Quantum Monte Carlo and Hubbard applications, and machine-learning methods for experimental data. Application examples include QMCPACK and DCA++, among others.
  3. Multiscale Materials Group —Delivers multiscale material models to a broad range of energy, transportation, and advanced manufacturing applications. Houses specific strengths in thermomechanics, phase-field modeling, molecular dynamics, and Density Functional Theory.
  4. Quantum Computational Science Group —Develops the fundamental quantum computer science, algorithms, and software interfaces needed to leverage quantum accelerators to advance scientific discovery.
  5. Quantum Information Science Group —Leverages experimental expertise in the implementation of quantum sensors, networks, and algorithms in quantum hardware platforms and testbeds. 

Advanced Computing Methods for Engineered Systems Section

Develops scalable and coupled algorithms for engineering, cybernetics, autonomous and complex systems applications.

  1.  Scalable Algorithms and Coupled Physics Group —Creates performance portable applications and supports algorithms and libraries for coupled physics simulations at scale. Leads in development for programming models, frameworks, and data mapping standards.
  2. Computational Systems Engineering and Cybernetics Group —Leads modeling for large-scale dynamical systems with applications in scalable control systems. Develops solutions for sensor data aggregation and methods for approaches to learning, control, and optimization.
  3. Multiphysics Modeling and Flows Group —Leads high-fidelity modeling and numerical tools development for fluid dynamics and complex flow physics, including turbulent, multiphase and reacting flows, fluid structure interactions, and computational mechanics and shockwave propagation.
  4. Autonomous and Complex Systems Group —Develops and deploys disruptive technologies at the extreme scale, such as multimodal sensing and pioneering algorithms for large laser arrays, signal processing algorithms, and online computing for sensing platforms.
  5. Computational Urban Sciences Group —Creates data-driven understanding of complex urban systems at all scales and leads in the development of related data analytics.

Advanced Computing for Health Sciences Section

Delivers scalable computational solutions to biomedical and healthcare delivery challenges.

  1. Biostatistics and Multiscale Systems Group —Develops statistical, machine-learning, and deep-learning methodologies for large-scale genomics, text, and imaging applications. Develops and incorporates AI and data-driven approaches at the intersections of molecular dynamics simulations that exploit the unique capabilities of the OLCF and the experimental validation capabilities at the Spallation Neutron Source, both Department of Energy Office of Science User Facilities.
  2. Multimodal Data Analytics Group —Leverages expertise in large-scale biomedical informatics and statistical genetics to build and use tools for healthcare needs. Creates scalable AI and machine-learning solutions for multidimensional, multimodal data in HPC environments applied to biomedicine and bioengineering. Includes privacy and biomedical informatics for supervised and unsupervised learning with healthcare data, specifically phenotyping, information extraction, medical imaging, and new outcomes such as recurrence.

Computer Science and Mathematics Division

The Computer Science and Mathematics Division delivers fundamental and applied research capabilities in applied mathematics and computer science, experimental computing systems, scalable algorithms and systems, artificial intelligence and machine learning, data management, workflow systems, analysis and visualization technologies, programming systems and environments, and systems science and engineering.

Mathematics in Computation Section

Delivers scalable and architecture-aware algorithms.

  1. Discrete Algorithms Group — Algorithms and foundations for discrete structures, including graph algorithms and discrete optimization.
  2. Data Analysis and Machine Learning Group — Algorithms and foundations for data analysis and machine learning.
  3. Multiscale Methods Group — Algorithms and foundations for methods spanning multiple time and length scales.
  4. Systems and Decision Sciences Group — Algorithms and foundations for engineered systems.

Advanced Computing Systems Research

Explores the impact that fundamental changes in computing technologies and systems will have on the DOE and ORNL mission.

  1. Beyond Moore Group — Explores the applicability of novel computing technologies for science.
  2. Architectures and Performance Group — Develops tools and methods for evaluating emerging computing architectures.
  3. Intelligent Systems and Facilities Group — Addresses the challenges associated with managing computing resources and facilities at scale.
  4. Programming Systems Group — Explores programming models, languages, and translation tools.
  5. Software Engineering Group — Engineers the next generation of scientific software to ensure quality, including reliability, trustworthiness, and usability.
  6. Application Engineering Group — Delivers advanced scientific applications with best-in-class methods, design, and implementation.

Data and AI Systems Research Section

Manages and gains knowledge from data.

  1. Visualization Group — Develops methods, tools, and technologies for visual data analysis.
  2. Learning Systems Group — Creates scalable tools to build models from data.
  3. Workflow Systems Group — Develops methods, tools, and technologies for the coordinated management of data movement.
  4. Performance Engineering Group — Rebuilds and optimizes data applications and systems, with an emphasis on scalability and advanced platforms to accelerate discovery.
  5. Data Engineering Group — Engineers data assets and systems, including data wrangling and system design, to drive scientific innovation.

National Center for Computational Sciences

The National Center for Computational Sciences (NCCS) provides state-of-the-art computational and data science infrastructure for technical and scientific professionals to accelerate scientific discovery and engineering advances across a broadrange of disciplines. As an important part of the broader High-Performance Computing (HPC) infrastructure, the division also hosts the Oak Ridge Leadership Computing Facility (OLCF), a Department of Energy Office of Science User Facility.

Systems Section

Administers and supports the division’s computing, networking, and storage systems.

  1. HPC Infrastructure Operations Group — Provides continuous monitoring, issue triaging and escalation, and general support of critical computational and facilities-related infrastructure.
  2. HPC Scalable Systems Group — Administers and supports system installation, deployment, acceptance, performance testing, upgrades, problem diagnosis, and troubleshooting.
  3. HPC Storage and Archive Group — Administers and supports high-speed parallel file systems and archive capabilities, which support the overall mission of leadership-class and scalable computing programs.
  4. HPC Infrastructure and Networking Group — Designs, implements, and operates all networking and system services common to all HPC and storage services in the division.
  5. HPC Clusters Group — Administers and supports the division’s HPC computing infrastructure, which includes system installation, deployment, acceptance, performance testing, upgrades, problem diagnosis, and troubleshooting.
  6. HPC Cybersecurity and Information Engineering Group — Develops tools and administers data management platforms to extract and analyze telemetry, event logs, and system state information to ensure security, operational, and laboratory policy compliance.

Operations Section

Provides support to the division’s infrastructure users and acquaints the public with the work conducted at the OLCF.

  1. User Assistance — Production Systems Group — Provides technical support, training, documentation and tools to NCCS users for systems that have entered full user operations.
  2. User Assistance – Pre-Production Systems Group — Ensures the functionality, performance, and usability of new NCCS systems through activities such as test development, acceptance, software installation, documentation, and early user support for all NCCS pre-production systems.
  3. Application Development and User Access Group — Develops and maintains large software applications and tools used by the staff and users of the division’s computational ecosystem. Provides access through these applications to the computational resources inside of the division. Ensures systems are compliant with laboratory and DOE User Facility policies.
  4. Platforms Group — Provides platforms as a service to NCCS users and staff so that they can develop, manage, and deliver their own applications that run on NCCS systems.
  5. Outreach and Communications Group — Develops and maintains communication materials for use with and by the NCCS sponsors and program managers that showcase NCCS capabilities and user research accomplishments.

Science Engagement Section

Partners NCCS users with experts in scientific domains and computation to obtain optimal scientific results from the center’s computational resources and systems.

  1. Advanced Computing for Chemistry and Materials Group — Partners with HPC and data analytics users in the chemical and materials sciences.
  2. Advanced Computing for Nuclear, Particles, and Astrophysics Group — Partners with HPC and data analytics users in nuclear physics, such as nuclear structure and quantum chromodynamics; high energy physics, such as particle physics; and astrophysics, such as stellar evolution and cosmology.
  3. Advanced Computing for Life Sciences and Engineering Group — Partners with HPC and data analytics users in climate science, geophysics, biology, biomedical sciences, and engineering.
  4. Algorithms and Performance Analysis Group — Partners with HPC and data analytics users on algorithmic and performance improvements and characterizes application performance and application requirements.

Advanced Technologies Section

Offers scientific, technical, operational, and thought leadership by developing, hardening, and deploying solutions for compute and data intensive computing environments. 

  1. AI Analytics Scalable Methods Group — Develops and deploys emerging large-scale data science and AI methods for scientific user programs and enables innovation through operational data analytics.
  2. Data Lifecycle and Scalable Workflows Group — Enables data stewardship and enriched scalable data access capabilities. Develops end-to-end scientific workflow technologies to user programs.
  3. Technology Integration Group — Identifies technical gaps in the computing and data sciences ecosystems and evaluates, develops, and deploys systems and solutions to enable scientific discovery.