Driving critical research in computer science through academic collaboration.
Centers with Intel
Intel Labs sponsors various science and technology centers at universities around the world in order to foster collaborations and development of communities among Intel and academia. We also collaborate on initiatives with the National Science Foundation and the Semiconductor Research Corporation.
Intelligent and Automated Connected Vehicles (IACV)
Based in Beijing, China, this research center focuses on the safety of autonomous vehicles as well as the human-machine interface of autonomous vehicles and the challenges brought by the new supporting laws and regulations.
Internet of Everything
Based in Taiwan at the National Taiwan University, this research center will serve as a conduit for research collaboration with the global and local industries to develop practical products and services.
Network on Intelligent Systems
Based in Europe, this research center will address the major open problems in the design and deployment of intelligent systems that function in the physical world.
Collaborative and Autonomous Resilient Systems
Based in Germany, this research center will investigate new opportunities for developing significant improvement to the security of autonomous platforms as well as self-defense capabilities of distributed systems.
An ecosystem of academic groups, government labs, research institutions, and companies around the world working with Intel to further neuromorphic computing and develop innovative AI applications.
Functional Materials and Devices beyond 3nm CMOS (FEINMAN)
The goal of the research center is to enable beyond CMOS materials for future integrated circuits beyond the CMOS transistor. The center aims to develop a) Ultra-low switching voltage materials/mechanisms for ferro-electricity and magneto-electricity b) high efficiency detection and transduction of magnetism using spin-orbit effects c) Integration of the magneto-electrics and spin-orbit materials to demonstrate sub 10 aJ, sub-100 mV switching of a MESO logic prototype.
The Intel Probabilistic Computing Center is focused on the: theoretical advancement for explainable AI based on Probabilistic Computing (KU Leuven, UCLA); computing architecture development for optimized DL and Probabilistic AI (Duke, KU Leuven); programming models and optimizations for combining neural networks and probabilistic inference (Northeastern, MIT); benchmarks and tools to evaluate performance of Bayesian Deep Networks (Oxford); and the applications of probabilistic computing for human intent estimation (CIMAT).
Wireless Autonomous Systems (WAS)
Aims to enhance end-to-end quality of service of safety critical autonomous services over wireless networks, through joint design of autonomy with wireless communication, and by exploiting machine learning techniques as a key enabler.
Based in Europe, this research center will work on advancing the functionality and safety of autonomous vehicles.
Data Systems AI Laboratory at MIT (DSAIL)
This is a partnership between MIT, Intel, Google, and Microsoft. The goal is to find ways to use AI technology to improve data systems and to use data systems to improve the practice of AI.
Networking Edge Computing
Network services are evolving from the traditional client-cloud to a client-edge-cloud model. This research will examine fundamental issues that arise from this shift by designing an overall
architecture that ensures end-to-end correctness, provides adequate privacy and security, and is built on the appropriate computational infrastructure.
The objective of the research center is to enable functional materials and devices for continuing Moore’s law beyond 3 nm. The overarching goal of the center is to enable the materials that lead to logic computing technology for integrated circuit applications with low voltage (<100 mV) and low switching energy (1aJ/bit).
Side Channel Academic Programming (SCAP)
With researchers based worldwide, this center focuses on the prevention and detection of speculative side channels.
Autonomous Driving Community of Practice (ADCoP)
Intel is funding significant research into Autonomous Driving Systems around the world. The Autonomous Driving Community of Practice (ADCoP) is a forum for these researchers to share their research and initiate collaboration, collectively multiplying the impact of Intel’s ADS portfolio. ADCoP hosts an annual FTF workshop, quarterly telecons and works with the research teams involved to help foster collaboration.
The goal of the ADEPT lab is to dramatically improve computing capability by reducing the cost and risk of designing custom silicon for new application areas. Our integrated 5-year research mission cuts across applications, programming systems, architecture, and hardware design and verification methodologies.
Brings together UC Berkeley researchers across the areas of computer vision, machine learning, natural language processing, planning, and robotics. BAIR includes over two dozen faculty and more than a hundred graduate students pursuing research on fundamental advances in the above areas as well as cross-cutting themes including multi-modal deep learning, human-compatible AI, and connecting AI with other scientific disciplines and the humanities.
Berkeley Wireless Research Center (BWRC)
The UC Berkeley Wireless Research Center is an established leader in university-industry-government research partnerships resulting in pioneering circuits and system-on-chip innovations for high-performance analog, digital, and mixed-signal applications.
A 5-year research project focused on solving the systems, machine learning, and security challenges required to create an open-source, general-purpose, secure stack that can make intelligent decisions on live data in real-time.
The Stanford SystemX Alliance is a collaboration between Stanford University and member industrial firms to produce world-class research and Ph.D. graduates with a view to enabling truly ubiquitous sensing, computing and communication with embedded intelligence.
Seeks unique data network architectures featuring an information plane using an Information-Centric Networking (ICN) approach and addressing discovery, movement, delivery, management, and protection of information within a network, along with the abstraction of an underlying communication plane creating opportunities for new efficiencies and optimizations across communications technologies that could also address latency and scale requirements.
Addresses the problem of effective software development for diverse hardware architectures through groundbreaking university research that will lead to a significant, measurable leap in software development productivity by partially or fully automating software development tasks that are currently performed by humans.
Intel NSF: Foundational Microarchitecture Research (FoMR)
FoMR seeks to advance research that has the following characteristics: (1) high IPC techniques ranging from microarchitecture to code generation; (2) “microarchitecture turbo” techniques that marshal chip resources and system memory bandwidth to accelerate sequential or single-threaded programs; and (3) techniques to support efficient compiler code generation. Advances in these areas promise to provide significant performance improvements that continue the trends characterized by Moore’s Law.
Intel NSF: Machine Learning for Wireless Networking Systems (MLWiNS)
This program 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.
Supporting long-term research focused on high performance, energy efficient microelectronics for end-to-end sensing and actuation, signal and information processing, communication, computing, and storage solutions that are cost-effective and secure.
ASCENT focuses on demonstration of foundational material synthesis routes and device technologies, novel heterogeneous integration (package and monolithic) schemes to support the next era of “functional hyper-scaling”.
The ADA Center will reignite system design innovation by drawing on opportunities in application driven architecture and system-driven technology advances, with support from agile system design frameworks that encompass programming languages to implementation technologies.
ComSenTer will develop the technologies for a future cellular infrastructure using hubs with massive spatial multiplexing, providing 1-100Gb/s to the end user, and, with 100-1000 simultaneous independently-modulated beams, aggregate hubs capacities in the 10's of Tb/s.
The CRISP grand challenge is to significantly lower the effort barrier for every day programmers to achieve highly portable, “bare-metal,” and understandable performance across a wide range of heterogeneous, IMS architectures.
The nanoelectronic COmputing REsearch (nCORE) program funds collaborative university research in the U.S. to develop key technologies to enable novel computing and storage paradigms with long-term impact on the semiconductor, electronics, computing, and defense industries. The nCORE program supports the National Strategic Computing Initiative (NSCI) through government-industry-academia collaborations. It will be driven by fundamental research on emerging materials and devices with the potential to achieve significantly improved efficiency, enhanced performance, and new functionalities, beyond the capability of conventional CMOS technologies. The new program is built upon the learning from the Nanoelectronics Research Initiative (NRI).
Transform the way people interact with engineered systems and address threats stemming from increasing reliance on computer and communication technologies.
Intel-NTU Connected Context Computing Center
This center aimed to create demonstrable machine-to-machine (M2M) technologies that can showcase the potential of these technologies to transform our everyday activities and environment. Located in Taiwan - NTU. 2010 - 2016.
Centered at Stanford University. The center sought to bring modern trends in computing (the cloud, crowd sourcing, hand-held computing) to bear on hybrids of computer graphics, animation, image understanding, and large-scale gaming. 2011-2015.
Centered at the University of Washington, the Pervasive Computing research center brought together research leaders in wireless communication and sensing, AI and ML, computer vision, HCI, and security. 2011-2016.
Centered at MIT, the Big Data research center is exploring data analytics to support data-intensive discovery including database management, analytics, and visualization support. 2012-2017.
Software Defined Networks (SDN)
Seeks to make networks more amenable to innovation by extending the benefits of SDN to carrier networks. Research vectors include SDN for carriers, processing traffic in software, services architecture, and deployment scenarios. 2014-2017.
Low Latency Architectures
Develop innovative techniques to reducing memory latency, create low latency storage systems, and accelerate progress in general-purpose microarchitectures, and accelerator architectures. 2014-2017.
Develop techniques for effectively summarizing the video egocentric cameras collect and develop solutions for extracting the useful information embedded in the raw data (first-person video, images, audio, and location) egocentric cameras collect and presenting this information to the user on demand. 2014-2017.
Developing novel algorithms, architectures, accelerators, circuits and power management techniques that optimally exploit randomized compressive measurements and compressed domain data processing for 2D/3D still/video/MRI images. 2014-2017.
Hubbed in Germany at Saarland University, the Institute focused on Visual Computing research, meaning the acquisition, modeling, processing, transmission, rendering, and display of visual and associated data. 2010-2016.
Based in England at University College London, Imperial College London, and Future Cities Catapult this center researches the compute fabric needed to support an urban Internet of Things at city scale. 2012-2017.
Based in Germany at TU Darmstadt, this center explores lightweight, cost-effective security and trust anchor primitives for IoT edge devices with integrated outputs into flexible and agile silicon prototypes. 2013-2017.
Based in Israel at Technion and Hebrew University, this center focuses on hardware/software innovations for accelerating Machine Learning and Cognitive Applications. 2013-2017.
Mobile Networking and Computing
Based in China at Tsinghua University, the research center for Mobile Networking and Computing is exploring advanced mobile network technologies to support typical applications in the next generation (5G) networks. 2015-2018.