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ANP-Flow: A System-Level Simulation and Performance Prediction Toolchain for Asynchronous Neuromorphic Hardware Enabling Co-Exploration

Energy-efficient neuromorphic hardware with ultralow power consumption is increasingly promising for edge–artificial intelligence (AI) applications. Most digital neuromorphic hardware is designed with asynchronous circuits as they naturally match the sparsity and event-driven features of neuromorphic computing. However...

Jian Zhang, Yuan Hua, Ji-Lin Zhang et al. · 1 citation

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