MixLLM: LLM Quantization with Global Mixed-precision between Output-features and Highly-efficient System Design Paper • 2412.14590 • Published 24 days ago • 13 • 5
MixLLM: LLM Quantization with Global Mixed-precision between Output-features and Highly-efficient System Design Paper • 2412.14590 • Published 24 days ago • 13
BatchLLM: Optimizing Large Batched LLM Inference with Global Prefix Sharing and Throughput-oriented Token Batching Paper • 2412.03594 • Published Nov 29, 2024
MixLLM: LLM Quantization with Global Mixed-precision between Output-features and Highly-efficient System Design Paper • 2412.14590 • Published 24 days ago • 13
MixLLM: LLM Quantization with Global Mixed-precision between Output-features and Highly-efficient System Design Paper • 2412.14590 • Published 24 days ago • 13 • 5
FP6-LLM: Efficiently Serving Large Language Models Through FP6-Centric Algorithm-System Co-Design Paper • 2401.14112 • Published Jan 25, 2024 • 18 • 7
FP6-LLM: Efficiently Serving Large Language Models Through FP6-Centric Algorithm-System Co-Design Paper • 2401.14112 • Published Jan 25, 2024 • 18
FP6-LLM: Efficiently Serving Large Language Models Through FP6-Centric Algorithm-System Co-Design Paper • 2401.14112 • Published Jan 25, 2024 • 18 • 7
Flash-LLM: Enabling Cost-Effective and Highly-Efficient Large Generative Model Inference with Unstructured Sparsity Paper • 2309.10285 • Published Sep 19, 2023 • 1
ZeroQuant(4+2): Redefining LLMs Quantization with a New FP6-Centric Strategy for Diverse Generative Tasks Paper • 2312.08583 • Published Dec 14, 2023 • 9
FP6-LLM: Efficiently Serving Large Language Models Through FP6-Centric Algorithm-System Co-Design Paper • 2401.14112 • Published Jan 25, 2024 • 18