A System Level Performance Evaluation for Superconducting Digital Systems

• Main Authors: Kundu, Joyjit, Bhattacharjee, Debjyoti, Josephsen, Nathan, Pokhrel, Ankit, De Silva, Udara, Guo, Wenzhe, Van Winckel, Steven, Brebels, Steven, Perumkunnil, Manu, Herr, Quentin, Herr, Anna
• Format: Journal Article
• Language: English
• Published: 13-11-2024
• Subjects: Computer Science - Artificial Intelligence; Computer Science - Emerging Technologies; Computer Science - Hardware Architecture
• DOI: 10.48550/arxiv.2411.08645

DATE 2025 Superconducting Digital (SCD) technology offers significant potential for
enhancing the performance of next generation large scale compute workloads. By
leveraging advanced lithography and a 300 mm platform, SCD devices can reduce
energy consumption and boost computational power. This paper presents a
cross-layer modeling approach to evaluate the system-level performance benefits
of SCD architectures for Large Language Model (LLM) training and inference. Our
findings, based on experimental data and Pulse Conserving Logic (PCL) design
principles, demonstrate substantial performance gain in both training and
inference. We are, thus, able to convincingly show that the SCD technology can
address memory and interconnect limitations of present day solutions for
next-generation compute systems.