The Computing Community Consortium (CCC) recently sponsored a Blue Sky Ideas Conference Track at the 16th International Symposium on Spatial & Temporal Databases Symposia (SSTD ’19), August 19-21, 2019 in Vienna, Austria. SSTD’19 discussed new and exciting research in spatial, temporal and spatio-temporal data management and related technologies with the goal to set future research directions. First prize – Understanding human mobility: A multi-modal and intelligent moving objects database Authors: Jianqiu Xu, Hua Lu and Ralf Hartmut Güting Second prize – Location-Based Social Simulation Authors: Hamdi Kavak, Joon-Seok Kim, Andrew Crooks, Dieter Pfoser, Carola Wenk and Andreas Züfle CCC provides travel awards to authors of the winning papers. We encourage you to apply […]
Computing Community Consortium Blog
The goal of the Computing Community Consortium (CCC) is to catalyze the computing research community to debate longer range, more audacious research challenges; to build consensus around research visions; to evolve the most promising visions toward clearly defined initiatives; and to work with the funding organizations to move challenges and visions toward funding initiatives. The purpose of this blog is to provide a more immediate, online mechanism for dissemination of visioning concepts and community discussion/debate about them.
Author Archive
Blue Sky Conference held at the Symposium on Spatial & Temporal Databases
September 10th, 2019 / in Announcements, Blue Sky / by Helen WrightUpcoming NSF Funding Opportunities
September 4th, 2019 / in Announcements, NSF, policy, research horizons, Research News, resources / by Helen WrightThe National Science Foundation (NSF) has a number of upcoming funding opportunities. Computational and Data-Enabled Science and Engineering (CDS&E) (PD 12-8084) Full Proposal Window: September 30, 2019 Advanced computational infrastructure and the ability to perform large-scale simulations and accumulate massive amounts of data have revolutionized scientific and engineering disciplines. The goal of the CDS&E program is to identify and capitalize on opportunities for major scientific and engineering breakthroughs through new computational and data analysis approaches. See more at this website here. Computer and Information Science and Engineering (CISE): Core Programs (NSF 19-589) Full Proposal Window: September 30, 2019 The NSF CISE Directorate supports research and education projects that develop new […]
NSF/Intel Partnership on Machine Learning for Wireless Networking Systems (WLWiNS) Program Webinar
August 28th, 2019 / in Announcements, NSF, policy, research horizons, Research News / by Helen WrightThe 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 […]
CCC Response to NITRD RFI “Information on Update to Strategic Computing Objectives”
August 22nd, 2019 / in Announcements, CCC, policy, Research News / by Helen WrightThe 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 […]
Deep Neural Network Acceleration Beyond Chips
August 21st, 2019 / in AI, Research News, resources, robotics / by Helen WrightThe 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 […]
ACM SIGARCH BLOG: Increasing Your Research Impact
August 13th, 2019 / in CCC, research horizons, Research News / by Helen WrightThe 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 […]







