Peer-reviewed paper
Catwalk: Unary Top-K for Efficient Ramp-No-Leak Neuron Design for Temporal Neural Networks
Catwalk introduces a unary top-K mechanism for temporal neural networks, targeting the ramp-no-leak neuron design. The result is a more efficient selection path that reduces overhead in the neuromorphic pipeline.
Abstract Summary
Catwalk introduces a unary top-K mechanism for temporal neural networks, targeting the ramp-no-leak neuron design. The result is a more efficient selection path that reduces overhead in the neuromorphic pipeline.
Research Context
This paper contributes to my research program in Temporal Neural Networks, neuromorphic computing, ISVLSI 2025. It is part of the broader work on efficient ML systems, hardware-software co-design, and deployment-aware computer architecture.