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cs.LG2025
SOLE: Hardware-Software Co-design of Softmax and LayerNorm for Efficient Transformer Inference
Wenxun Wang, Shuchang Zhou, Wenyu Sun +2
Transformers have shown remarkable performance in both natural language processing (NLP) and computer vision (CV) tasks. However, their real-time inference speed and efficiency are…
cs.LG2025
MoESD: Unveil Speculative Decoding's Potential for Accelerating Sparse MoE
Zongle Huang, Lei Zhu, Zongyuan Zhan +5
Large Language Models (LLMs) have achieved remarkable success across many applications, with Mixture of Experts (MoE) models demonstrating great potential. Compared to traditional…
cs.LG2022
Block-Wise Dynamic-Precision Neural Network Training Acceleration via Online Quantization Sensitivity Analytics
Ruoyang Liu, Chenhan Wei, Yixiong Yang +3
Data quantization is an effective method to accelerate neural network training and reduce power consumption. However, it is challenging to perform low-bit quantized training: the c…