IEEE Rebooting Computing Competition

IEEE Rebooting Computing Competition
Name	IEEE Rebooting Computing Competition
Established	2014
Organizer	IEEE
Sponsor	Microsoft Research, Intel Corporation, Google, IBM
Location	Global

Contents

IEEE Rebooting Computing Competition The IEEE Rebooting Computing Competition is an international contest organized by the IEEE to stimulate innovation in computing architectures, systems, and algorithms. The competition encourages collaboration among researchers from institutions such as Massachusetts Institute of Technology, Stanford University, University of California, Berkeley, Carnegie Mellon University, and industry partners including Microsoft Research, Intel Corporation, Google, and IBM Research. Entrants address challenges inspired by initiatives like the ENIAC legacy, the Human Brain Project, advances at Los Alamos National Laboratory, and concepts promoted by the National Science Foundation.

Overview

The competition solicits proposals and prototypes that rethink computing paradigms influenced by milestones such as Moore's Law, the von Neumann architecture, the Transistor invention at Bell Labs, and the rise of projects at DARPA. Submissions span hardware concepts related to initiatives at Sandia National Laboratories and Lawrence Livermore National Laboratory, software approaches aligned with work from OpenAI and DeepMind, and cross-disciplinary ideas akin to research at ETH Zurich and Tsinghua University. The program amplifies collaboration among participants from University of Cambridge, University of Oxford, Imperial College London, Peking University, and National University of Singapore.

Launched amid concerns about limits to scaling championed by figures such as Gordon Moore and debates around the future of the Intel 4004 lineage, the contest emerged from IEEE initiatives similar to conferences like International Solid-State Circuits Conference, International Conference on Computer Design, and workshops at SIGARCH. Early goals mirrored agendas from the President's Council of Advisors on Science and Technology and aligned with roadmaps from Semiconductor Research Corporation. Objectives include fostering alternatives to the von Neumann bottleneck, promoting energy-efficient designs inspired by the Blue Gene project at IBM, and encouraging neuromorphic efforts reminiscent of SpiNNaker and TrueNorth systems.

The competition organizes entries into categories comparable to sessions at NeurIPS, International Conference on Machine Learning, and ACM/IEEE International Symposium on Computer Architecture. Typical categories include novel architectures similar to projects at ARM Holdings and RISC-V, algorithms for heterogeneous platforms used by NVIDIA Corporation and AMD, and co-design challenges that echo collaborations at Microsoft Research Cambridge and Google DeepMind. Submissions may be prototypes, detailed designs, or simulation studies echoing methods from ANSYS users and modeling approaches found at Lawrence Berkeley National Laboratory.

Eligibility mirrors other IEEE competitions and invites teams from institutions such as California Institute of Technology, University of Illinois Urbana-Champaign, Georgia Institute of Technology, and companies like Apple Inc. and Facebook (Meta Platforms). Participants often include postdoctoral researchers affiliated with Max Planck Society, PhD students from Princeton University, and engineering teams from Texas Instruments. Regional chapters including IEEE Computer Society sections and student branches from IEEE Young Professionals coordinate local participation and outreach.

Judging panels draw experts from organizations like IEEE Computer Society, ACM, NIST, and industrial labs such as Intel Labs and Google Research. Criteria emphasize novelty reminiscent of breakthroughs at Bell Labs, technical merit comparable to publications in Communications of the ACM, scalability echoing initiatives at Amazon Web Services, and energy efficiency measured against benchmarks used by TOP500 and Green500. Awards include grand prizes, honorable mentions, travel grants to venues like International Conference on Computer Vision, and collaboration opportunities with sponsors such as IBM Research and Microsoft Research.

Past winning teams have included university groups from University of Michigan, University of Toronto, and University of Washington as well as industry consortia involving ARM Holdings and Xilinx. Projects have ranged from neuromorphic accelerators inspired by Human Brain Project architectures, quantum-hybrid control systems reflecting work at Google Quantum AI, and domain-specific accelerators akin to designs at NVIDIA. Some awardees later collaborated with initiatives at National Renewable Energy Laboratory and contributed to consortiums like RISC-V International and OpenPOWER Foundation. These projects influenced roadmaps at Semiconductor Industry Association partners and informed curricula at institutions such as Harvard University and Yale University.

Category:Competitions