About FABRIC

FABRIC (FABRIC is Adaptive ProgrammaBle Research Infrastructure for Computer Science and Science Applications) is an International infrastructure that enables cutting-edge experimentation and research at-scale in the areas of networking, cybersecurity, distributed computing, storage, virtual reality, 5G, machine learning, and science applications.

The FABRIC infrastructure is a distributed set of equipment at commercial collocation spaces, national labs and campuses. Each of the 29 FABRIC sites has large amounts of compute and storage, interconnected by high speed, dedicated optical links. It also connects to specialized testbeds (5G/IoT PAWR, NSF Clouds), the Internet and high-performance computing facilities to create a rich environment for a wide variety of experimental activities.

FABRIC Across Borders (FAB) extends the network to 4 additional nodes in Asia and Europe.

FABRIC is funded by NSF grants CNS-1935966, CNS-2029176, CNS-2029200, CNS-2029235, CNS-2029260, CNS-2029261, CNS-2330891.

FABRIC Capabilities

FABRIC Enables New Internet and Science Applications

Encourages a multidisciplinary approach to designing the next generation Internet supporting end users as well as science domains that depend on large-scale intelligent networks. Provides access to cutting-edge programmable network technologies, like P4 and OpenFlow.

FABRIC Advances Cybersecurity

Enables at-scale, more realistic research by peering with production networks to observe behavior.

FABRIC Integrates Machine Learning & Artificial Intelligence

Enables novel approaches to distributed and network systems control and management by integrating Machine Learning capabilities.

FABRIC Integrates HPC, Wireless, and IoT

Creates a diverse environment combining programmable core and edge networks, large computational resources, 5G and IoT capabilities.

FABRIC Promotes Education

FABRIC helps train the next generation of computer science researchers.

What is FABRIC?

FABRIC helps train the next generation of computer science researchers.

Presentation

Webinar

About FAB

FABRIC Across Borders (FAB) is an extension of the FABRIC testbed connecting the core North America infrastructure to four nodes in Asia, Europe, and South America. By creating the networks needed to move vast amounts of data across oceans and time zones seamlessly and securely, the project enables international collaboration to speed scientific discovery.

Science Applications

FAB is driven by science needs in fields that are pushing the limits of what today’s Internet can support. It offers a testbed to explore ways to handle and share massive amounts of data generated by powerful new scientific instruments around the globe.

FAB is built around use cases led by scientific partners in five areas:

Smart Cities	Sensing and Computing	SAGE • University of Antwerp • University of Bristol
Weather	Weather and Climate Prediction	University of Miami • CPTECH Center for Weather Forecast and Climatic Studies, Brazil
Physics	High Energy Physics	Large Hadron Collider, CERN • University of Chicago
Space	Astronomy and cosmology	Legacy Survey of Space and Time • Cosmic Microwave Background-Stage 4
Computer Science	Private 5G networks, censorship evasion, network competition and sharing, software-defined networking, P4 programming	University of Tokyo • Clemson University • University of Kentucky • KREONET

International Connections

FAB will connect FABRIC to five global partners:

University of Tokyo	Japan
CERN, the European Organization for Nuclear Research	Switzerland
University of Bristol	U.K.
University of Amsterdam	The Netherlands
CPTEC/INPE	Brazil

High-speed links will be provided by NSF’s International Research & Education Network Connections:

TransPAC	U.S. to Asia
StarLight	U.S. to Europe
Networks for European, American, and African Research (NEAAR)	U.S. to Europe and Africa
AmLight-ExP	U.S. to South America and Africa

FAB Core Team

Paul Ruth	RENCI
Anita Nikolich	University of Illinois Urbana Champaign
Jim Griffioen	University of Kentucky
Kuang-Ching Wang	Clemson University
Inder Monga	Lawrence Berkeley National Laboratory
Rob Gardner	University of Chicago