Abstract
Multi-core neuromorphic processors are becoming increasingly significant due to their energy-efficient local computing and scalable modular architecture, particularly for event-based processing applications. However, minimizing the cost of inter-core communication, which accounts for the majority of energy usage, remains a challenging issue. Beyond optimizing circuit design at lower abstraction levels, an efficient multicast addressing scheme is crucial. We propose a hierarchical bit string encoding scheme that largely expands the addressing capability of state-of-the-art symbol-based schemes for the same number of routing bits. When put at work with a real neuromorphic task, this hierarchical bit string encoding achieves a reduction in area cost by approximately 29% and decreases energy consumption by about 50%.
| Original language | English |
|---|---|
| Title of host publication | IEEE International Symposium on Circuits and Systems (ISCAS) |
| DOIs | |
| Publication status | Published - 27 Jun 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Multi-core neuromorphic processors
- Multicast
- Hierarchical bit string
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