• NITRD Coordination Areas

    The Networking and Information Technology Research and Development (NITRD) Program's member agencies coordinate their NITRD research activities and plans by Program Component Areas (PCAs) or program focus areas. For each PCA, agency representatives meet in an Interagency Working Group (IWG) to exchange information and collaborate on research plans and activities such as testbeds, workshops, and cooperative solicitations.

    NITRD Coordination Areas

FC-COI-2019

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  • Future Computing Community of Interest Meeting

    The Future Computing (FC) Community of Interest Meeting will explore the computing landscape for the coming decade and beyond, along with emerging and future application drivers, to inform agencies and to identify potential opportunities as well as gaps.


    Future Computing Community of Interest Meeting

Future Computing Community of Interest Meeting

August 5-6, 2019

NITRD NCO

490 L’Enfant Plaza SW, Suite 8001, Washington, DC


Logistics

Goal

The Future Computing (FC) Community of Interest Meeting will explore the computing landscape for the coming decade and beyond, along with emerging and future application drivers, to inform agencies and to identify potential opportunities as well as gaps. It will also examine new software concepts needed for the effective use of advances that come with the future computing systems to ensure that the federal government is poised to respond to unanticipated challenges and opportunities.

Rationale

There is much uncertainty in the HEC community as clock rate increases attributed to Moore’s law and Dennard are expected to end in the near future. The increase in feature count is currently slowing and will likely end within a few years. In this period of uncertainty, it is essential for the community to understand and embrace technologies coming to fruition in both the near- and long-term that provide a path forward for HEC in the absence of Moore’s Law and Dennard scaling. The impact of data analytics (including the use of artificial intelligence/machine learning), involving the movement, manipulation and storage of significant amounts of data has had a disruptive effect on high-end computing as well. The public, academic and private sector all need to be prepared for these new computing modalities from a hardware, software and workforce perspective.

Reference Materials