← Search

Sangwoo Hwang

2 accepted papers

2026

PsumQuant: In-line Post-training Partial Sum Quantizer for Energy Efficient NPU Inference

ICML 2026poster

The rapid growth of deep neural networks (DNNs) has intensified the demand for efficient hardware acceleration under quantization. While prior research has successfully reduced weight and activation precision, partial sums generated during accumulation often retain high precision, resulting in signi…

Cited by 0SourceScholar
2024

SpikedAttention: Training-Free and Fully Spike-Driven Transformer-to-SNN Conversion with Winner-Oriented Spike Shift for Softmax Operation

NeurIPS 2024poster

Event-driven spiking neural networks(SNNs) are promising neural networks that reduce the energy consumption of continuously growing AI models. Recently, keeping pace with the development of transformers, transformer-based SNNs were presented. Due to the incompatibility of self-attention with spikes,…