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Building on its capabilities in data-intensive computing and computational science, Brookhaven National Laboratory is embarking upon a major new Computational Science Initiative.

Advances in computational science, data management and analysis have been a key factor in the success of Brookhaven Lab's scientific programs at the Relativistic Heavy Ion Collider (RHIC), the National Synchrotron Light Source (NSLS), the Center for Functional Nanomaterials (CFN), and in biological, atmospheric, and energy systems science, as well as our collaborative participation in international research endeavors, such as the ATLAS experiment at Europe's Large Hadron Collider.

The Computational Science Initiative (CSI) brings together under one umbrella the expertise that has driven this success to foster cross-disciplinary collaborations to address the next generation of scientific challenges posed by facilities such as the new National Synchrotron Light Source II (NSLS II). A particular focus of CSI's work will be the research, development and deployment of novel methods and algorithms for the timely analysis and interpretation of high volume, high velocity, heterogeneous scientific data created by experimental, observational and computational facilities to accelerate and advance scientific discovery. CSI is hereby taking an integrated approach, providing capabilities from leading edge research to multi-disciplinary teams that deliver operational data analysis capabilities to the scientific user communities.

Enabling Capabilities

Computer Science and Mathematics—fundamental research into novel methods and algorithm in support of large-scale, multi-modal, and streaming data analysis. Novel solutions for long term data curation and active reuse. Approaches to enable energy efficient, extreme-scale numerical modeling specifically in computational materials science, chemistry, lattice quantum chromo dynamics and fusion.

The BNL Scientific Data and Computing Center, housing the latest systems in high-performance and data-intensive computing, data storage, and networking, offering everything from novel research platforms to highly reliable production services.

Translational Capabilities

The Computational Science Laboratory, a collaborative space for the development of advanced algorithms and their characterization and optimization, also brings together computer scientists, mathematicians, and leading computational scientists to develop next-generation numerical simulation models

The Center for Data Driven Discovery (C3D), a multi-disciplinary center for the development, deployment, and operation of data-intensive discovery services for science, national security, and industry

A Multi-disciplinary, Collaborative Approach

The CSI philosophy is a multi-disciplinary and collaborative approach to scientific research and development, with research targeted at and informed by the key challenges observed in close interactions with our clients in science, national security agencies, and industry. Our success is measured in equal parts by the advancement we can bring to computer science and mathematics, as well as by the transformational impact we have on our clients’ mission space.

The CSI brings together under one umbrella the expertise that fosters cross-disciplinary collaboration and makes optimal use of existing technologies, while also leading the development of new tools and methods that will benefit science both within and beyond the Laboratory. Key partners include nearby universities such as Columbia, Cornell, New York University, Stony Brook, and Yale, as well as IBM Research.

Strategic Partnerships

Computational scientists at Brookhaven will also seek to establish partnerships with key players in academia and industry (e.g. Stony Brook University’s Institute for Advanced Computational Science, Rensselaer Polytechnic Institute, Oak Ridge National Laboratory, IBM, and Intel). One existing example of a successful partnership is the collaboration of Brookhaven Lab’s high-energy and nuclear physics research groups with IBM that led to the development of the BlueGene supercomputing architecture now used on the world’s most powerful commercially available supercomputers.

More about strategic partnerships
  1. APR



    Computational Science Initiative Event

    "The Exascale Computing Project: Status and Next Steps"

    Presented by Dr. Doug Kothe and Stephen Lee, ORNL/LANL

    2:30 pm, Seminar Room, Bldg. 725

    Wednesday, April 4, 2018, 2:30 pm

    Hosted by: Kerstin Kleese van Dam

    The Exascale Computing Project (ECP) is focused on accelerating the delivery of a capable exascale computing ecosystem to provide breakthrough solutions that can address our most critical challenges in scientific discovery, energy assurance, economic competitiveness, and national security. ECP is a joint effort of two DOE organizations: the Office of Science (SC) and the National Nuclear Security Administration (NNSA). In this context, "capable" means that a wide range of applications will be able to use the systems developed through ECP, ensuring that both science and security needs will be addressed. The term "ecosystem" shows that the goal is not just more powerful machines, but all of the methods and tools needed to ensure effective use of the ECP-enabled exascale systems to be acquired by DOE national laboratories. Current plans call for delivery of the first exascale system to Argonne National Laboratory in 2021, with additional exascale systems to follow at other SC and NNSA laboratories over the next several years to meet identified mission needs. ECP's work encompasses the development of applications, software technologies, and hardware technologies and architectures. This work is carried out by teams that leverage the diverse capabilities of the national laboratories (such as Brookhaven National Laboratory), universities, and industry. These teams are presently delivering advances in all three of these focus areas. A brief overview of the goals and scope of the ECP will be given along with highlights of recent R&D activities, deliverables (milestones), and accomplishments for each of the three focus areas. Near term plans will also be addressed, including the technical challenges foreseen on the horizon.

  1. AUG



    2018 New York Scientific Data Summit (NYSDS)

    August 6-8, 2018