Track Chair
TBC
This track explores cutting-edge approaches to designing multicore system-on-chip (SoC) platforms inspired by the structure and function of biological neural systems. Neuromorphic computing offers promising solutions for ultra-low-power, event-driven, and adaptive processing—especially for edge AI, robotics, and sensor-rich environments. The track welcomes contributions that advance hardware and software co-design for brain-inspired architectures, spanning from spiking neural networks to emerging memory technologies. Topics of Interest Include:
- Neuromorphic hardware design:
- Spiking neural network (SNN) accelerators
- Event-driven and asynchronous multicore architectures
- Memristive and synaptic device integration
- System-level integration:
- Co-design of neuromorphic cores with conventional multicore SoCs
- Hybrid analog-digital processing frameworks
- Scalable interconnects and communication models
- Applications and workloads:
- Edge AI, autonomous systems, and real-time sensory processing
- Brain-inspired learning and adaptation mechanisms
- Energy-efficient cognitive computing
- Tools and simulation frameworks:
- Neuromorphic design automation and benchmarking
- Emulators and simulators for brain-inspired systems
- Comparative analysis with conventional AI accelerators
