SHF: Small: Computer Aided Design Methodologies and Tools for Superconducting Single Flux Quantum Technology

University Of Southern California, Los Angeles CA

Investigators

Abstract

Advances in "beyond-CMOS" device technologies and corresponding logic families are now seen as a key step towards achieving the next major leap in high-performance computing. The research challenges and opportunities described in this research provide directions for developing many aspects of a very promising "beyond-CMOS" technology, which can result in extremely high performance, yet energy-efficient, computing system, and thereby, ensure sustainability of the information technology ecosystem. Education, Outreach, and Training Programs include development of new educational modules; recruitment of minority and under-represented students; as well as undergraduate learning and research internship opportunities for undergraduates. The technical goal of this project is to investigate the state-of-the-art in design and optimization of superconducting DC-powered single flux quantum (SFQ) logic circuits and draw up a comprehensive research plan for developing a standard cell-based design methodology and supporting computer-aided design tools for the SFQ logic at the register-transfer-level. In the process, this project will analyze similarities and differences between the SFQ logic and standard digital CMOS logic fabrics, investigate various problems related to the synthesis, optimization and physical design of SFQ logic gates and circuits, and finally produce a number of computer-aided design techniques and prototype software tools for proof-of-concept demonstrations, including a standard cell characterization tool, a static timing and power analysis tool, a frontend logic synthesis, and a backend placement and clock network design tool. In short, this research aims to achieve major strides in the development of advanced design automation technologies in support of large-scale superconductive SFQ digital electronics to meet the needs of future energy-efficient, high-performance exa-scale computing systems.