FuSe2 Topic 1: Domain-specific probabilistic computing with stochastic antiferromagnetic tunnel junctions

Information

  • NSF Award
  • 2425538
Owner
  • Award Id
    2425538
  • Award Effective Date
    9/1/2024 - 6 months ago
  • Award Expiration Date
    8/31/2027 - 2 years from now
  • Award Amount
    $ 607,900.00
  • Award Instrument
    Continuing Grant

FuSe2 Topic 1: Domain-specific probabilistic computing with stochastic antiferromagnetic tunnel junctions

As society increasingly relies on digital technologies, the growing energy consumption of computing systems makes their continued scaling unsustainable. At the same time, conventional computers face fundamental challenges in solving many important computing problems related to optimization. A possible solution to these challenges is to fundamentally change the architecture of computing systems. A promising example of such unconventional computing approaches is probabilistic (p-) computing, which uses a network of probabilistic bits that collectively evolve towards the network’s energy minima, which are designed to correspond to the solution(s) of the computing problem of interest. However, the realization of large-scale p-computers that provide computational advantage over conventional computers still requires improvements in the energy efficiency and speed of existing p-bits. This project will address this need by developing p-bits based on a new type of magnetic device, referred to as an antiferromagnetic tunnel junction. These devices have inherently faster dynamics than existing magnetic p-bits, making them excellent candidates for p-bit implementation. The project brings together experts in materials, devices, circuits, and architectures, who will co-design the proposed p-bits and explore domain-specific computing architectures that combine these p-bits with state-of-the-art semiconductor chip technology. <br/><br/>The results of this project will impact a broad range of commercial markets, which face hard computational tasks related to combinatorial optimization. Applications of the developed domain-specific probabilistic computers can include logistics, transportation networks, wireless infrastructure, and chip design, to name a few. In addition, this project also contains educational components for semiconductor workforce development. These plans include collaborative development of a new course focusing on next-generation computing based on emerging materials. The project will also collaborate both with external professional societies as well as with local university resources, to provide opportunities for high school, undergraduate, and community college students to gain exposure to scientific research and training in magnetism and advanced computing. Through its combined research and workforce development efforts, the project will contribute to the continued leadership of the United States in the important areas of microelectronics technology, chip design, and advanced computing systems.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

  • Program Officer
    Jason Hallstromjhallstr@nsf.gov7032920000
  • Min Amd Letter Date
    9/10/2024 - 6 months ago
  • Max Amd Letter Date
    9/10/2024 - 6 months ago
  • ARRA Amount

Institutions

  • Name
    Northwestern University
  • City
    EVANSTON
  • State
    IL
  • Country
    United States
  • Address
    633 CLARK ST
  • Postal Code
    602080001
  • Phone Number
    3125037955

Investigators

  • First Name
    Kerem
  • Last Name
    Camsari
  • Email Address
    camsari@ece.ucsb.edu
  • Start Date
    9/10/2024 12:00:00 AM
  • First Name
    Pedram
  • Last Name
    Khalili Amiri
  • Email Address
    pedram@northwestern.edu
  • Start Date
    9/10/2024 12:00:00 AM
  • First Name
    Joseph
  • Last Name
    Friedman
  • Email Address
    joseph.friedman@utdallas.edu
  • Start Date
    9/10/2024 12:00:00 AM
  • First Name
    Jean Anne
  • Last Name
    Incorvia
  • Email Address
    incorvia@austin.utexas.edu
  • Start Date
    9/10/2024 12:00:00 AM

Program Element

  • Text
    NSF-Samsung Partnership

Program Reference

  • Text
    Microelectronics and Semiconductors