Search Results for author:
Found 2 papers, 1 papers with code
CMoE: Fast Carving of Mixture-of-Experts for Efficient LLM Inference
Large language models (LLMs) achieve impressive performance by scaling model parameters, but this comes with significant inference overhead.
MixPE: Quantization and Hardware Co-design for Efficient LLM Inference
Transformer-based large language models (LLMs) have achieved remarkable success as model sizes continue to grow, yet their deployment remains challenging due to significant computational and memory demands.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
