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A Transformative Co-Design Approach to Materials and Computer Architecture Research

Threadwork is an innovative co-design approach that seeks to transform the process by which we conduct microelectronics research. We interpret co-design as a way to frame new opportunities in device-oriented materials R&D that can change the microelectronics paradigm applied to computer architectures and a related set of application.

Threadwork is focused on a co-design approach that encompasses neuromorphic computing, systems architecture, and datacentric applications. One class of applications that can benefit from an innovative co-design approach is the set of large detectors on future high energy physics (HEP) and nuclear physics (NP) experiments, to which belong some of the most complex large-scale engineered devices in the world.

Threadwork addresses the AI needs for the HEP and NP detectors via a systems approach of focusing on the relevant AI technologies and chip-to-chip interconnects. In particular, Threadwork is organized around an innovative approach to co-design for neuromorphic devices and terahertz interconnects coupled with HEP and NP detectors via a simulation framework. Our approach entails all-to-all relationships — very different from the current status quo, which involves relationships only between adjacent layers.

With respect to the Microelectronics BRN, Threadwork is focused on:

  • Flip the current paradigm (PRD 1), with a focus on developing all-to-all relationships among abstraction elements
  • Revolutionize memory and data storage (PRD2), with a focus on neuromorphic devices
  • Reimagine information flow unconstrained by interconnects (PRD3), with a focus on chip-to-chip interconnect

This project is funded by DOE ASCR and BES, as part of the Microelectronics Program.

Threadwork Leadership

Valerie Taylor, PI
Argonne National Laboratory

Anand Bhattacharya, Co-Lead, Materials Research Team
Argonne National Laboratory

Mark Hersam, Co-Lead, Materials Research Team
Northwestern University

Andrew Chien, Lead, Simulations Team
The University of Chicago

Salman Habib, Lead, Application Team
Argonne National Laboratory