The National Science Foundation (NSF) is holding a webinar on September 11, 2019 at 2:00 PM ET for the NSF/Intel Partnership on Machine Learning for Wireless Networking Systems (MLWiNS) solicitation NSF 19-591, submission requirements, and program updates. The NSF/Intel Partnership on Machine Learning for Wireless Networking Systems (MLWiNS) seeks to accelerate fundamental, broad-based research on wireless-specific machine learning (ML) techniques, towards a new wireless system and architecture design, which can dynamically access shared spectrum, efficiently operate with limited radio and network resources, and scale to address the diverse and stringent quality-of-service requirements of future wireless applications. In parallel, this program also targets research on reliable distributed ML by addressing the challenge […]

The following post was contributed by CCC Director,  Ann Schwartz Drobnis.  The Networking and Information Technology Research and Development (NITRD) National Coordination Office (NCO), on behalf of Federal agencies and the NITRD National Science and Technology Council’s (NSTC) Fast-Track Action Committee (FTAC) on Strategic Computing (SC), put out a Request for Information (RFI) from the public to update for the Strategic Computing R&D goals and approaches. The Computing Community Consortium (CCC) responded to the RFI on behalf of the community. Some snippets from CCC’s response: Many—if not most—of the benefits that information technology has provided to society have in turn depended on tremendous progress in technology (Moore’s Law) and in hardware designs for compute, storage, and communication. Future information […]

The following blog was written by Computing Community Consortium (CCC) Chair Mark D. Hill from the University of Wisconsin Madison.  This week Cerebras announced a bold design to accelerate deep neural networks with silicon that is not cut into chips. AI and Moore’s Law: Artificial Intelligence (AI) is much in the news for what it can do to today and the promise of what it can do tomorrow (CCC/AAAI 20-Year AI Roadmap). Over half a century, AI innovation has been abetted by a million-fold progress in computer system cost-performance and parallelism. For decades, computer benefits came transparently via repeated doubling of processor performance (popularly called “Moore’s Law”). For the last decade, however, AI–especially for the great successes of […]

The following blog was originally posted in ACM SIGARCH on August 12, 2019. It is written by Computing Community Consortium (CCC) Chair Mark D. Hill from the University of Wisconsin Madison. Hill is the recipient of the 2019 Eckert-Mauchly award, a lifetime achievement award in computer architecture.  Many works present their results; this blog post seeks to aid you in developing your own great results, especially in computer architecture and systems. I learned these lessons over a career leading to an Eckert-Mauchly Award (acceptance speech). I structure this blog post with the scientific method in four steps: Pick a good problem. Develop insights and first hypotheses. Test and refine hypotheses. Repeat steps as needed. Pick A Good Problem  The first step to […]

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CCC Chair Mark D. Hill, CCC Vice-Chair Liz Bradley, and CCC Director Ann Schwartz Drobnis provided significant contributions to this post. The Computing Community Consortium (CCC) is pleased to release the completed Artificial Intelligence (AI) Roadmap, titled A 20-Year Community Roadmap for AI Research in the US! An HTML version is available here. This roadmap is the result of a year long effort by the CCC and over 100 members of the research community, led by Yolanda Gil (University of Southern California and President of AAAI) and Bart Selman (Cornell University and President Elect of AAAI). Comments on a draft report of this roadmap were requested in May 2019. Thank you to everyone in the […]