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2026
ReSCom: A Reconfigurable Spiking Neural Network Accelerator Using Stochastic Computing
This paper presents ReSCom, a reconfigurable SNN accelerator that leverages stochastic computing to reduce hardware complexity while maintaining stable inference.
SupraSNN: Exploiting Synapse-Level Parallelism in Spiking Neural Network Accelerators through Co-Optimized Mapping and Scheduling
This paper introduces SupraSNN, a superscalar-inspired architecture for efficient execution of Spiking Neural Networks (SNNs) on physical hardware.
ChroNoC: A Tableless TDM Circuit-Switched NoC With Delay-Aware Deployment for Time-Sensitive Neuromorphic Computing
This paper proposes a hardware-software co-design to improve the efficiency and performance of neuromorphic architectures.
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