Multiply-and-Fire (MNF): An Event-driven Sparse Neural Network Accelerator

no code implementations • 20 Apr 2022 • Miao Yu, Tingting Xiang, Venkata Pavan Kumar Miriyala, Trevor E. Carlson

Machine learning, particularly deep neural network inference, has become a vital workload for many computing systems, from data centers and HPC systems to edge-based computing.

Ultra-low power on-chip learning of speech commands with phase-change memories

no code implementations • 21 Oct 2020 • Venkata Pavan Kumar Miriyala, Masatoshi Ishii

Embedding artificial intelligence at the edge (edge-AI) is an elegant solution to tackle the power and latency issues in the rapidly expanding Internet of Things.

You Only Spike Once: Improving Energy-Efficient Neuromorphic Inference to ANN-Level Accuracy

no code implementations • 3 Jun 2020 • Srivatsa P, Kyle Timothy Ng Chu, Burin Amornpaisannon, Yaswanth Tavva, Venkata Pavan Kumar Miriyala, Jibin Wu, Malu Zhang, Haizhou Li, Trevor E. Carlson

Rate-encoded SNNs could be seen as inefficient as an encoding scheme because it involves the transmission of a large number of spikes.