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Junyao Zhang

Publications and source records attributed to Junyao Zhang.

20 records · Page 2Linked to original sources

A Majority Logic Synthesis Framework For Single Flux Quantum Circuits

Exascale computing and its associated applications have required increasing degrees of efficiency. Semiconductor-Transistor-based Circuits (STbCs) have struggled with increasing the GHz frequency while dealing with power dissipation issues. Emerging as an alternative to STbC, single flux quantum (SFQ) logic in the superconducting electrons (SCE) technology promises higher-speed clock frequencies at ultra-low power consumption. However, its quantized pulse-based operation and high environmental requirements, process variations and other SFQ-specific non-idealities are the significant causes of logic error for SFQ circuits. A suitable method of minimizing the impact of the afore-mentioned error sources is to minimize the number of Josephson Junctions (JJs) in the circuits, hence an essential part of the design flow of large SFQ circuits. This paper presents a novel SFQ logic synthesis framework that given a netlist, offers an automated mapping solution including majority (MAJ) logic with the goal of minimizing the number of JJs, while catering to the unique characteristics and requirements of the design. Our experiments confirm that our synthesis framework significantly outperforms the state-of-the-art academic SFQ technology mapper, namely reducing the number of JJs on average by 35.0%.

cs.LO↗

Trust-aware Control for Intelligent Transportation Systems

Many intelligent transportation systems are multi-agent systems, i.e., both the traffic participants and the subsystems within the transportation infrastructure can be modeled as interacting agents. The use of AI-based methods to achieve coordination among the different agents systems can provide greater safety over transportation systems containing only human-operated vehicles, and also improve the system efficiency in terms of traffic throughput, sensing range, and enabling collaborative tasks. However, increased autonomy makes the transportation infrastructure vulnerable to compromised vehicular agents or infrastructure. This paper proposes a new framework by embedding the trust authority into transportation infrastructure to systematically quantify the trustworthiness of agents using an epistemic logic known as subjective logic. In this paper, we make the following novel contributions: (i) We propose a framework for using the quantified trustworthiness of agents to enable trust-aware coordination and control. (ii) We demonstrate how to synthesize trust-aware controllers using an approach based on reinforcement learning. (iii) We comprehensively analyze an autonomous intersection management (AIM) case study and develop a trust-aware version called AIM-Trust that leads to lower accident rates in scenarios consisting of a mixture of trusted and untrusted agents.

cs.AI↗