Search Results for author: Dacheng Li

Found 9 papers, 7 papers with code

Fairness in Serving Large Language Models

1 code implementation31 Dec 2023 Ying Sheng, Shiyi Cao, Dacheng Li, Banghua Zhu, Zhuohan Li, Danyang Zhuo, Joseph E. Gonzalez, Ion Stoica

High-demand LLM inference services (e. g., ChatGPT and BARD) support a wide range of requests from short chat conversations to long document reading.

Fairness Scheduling

S-LoRA: Serving Thousands of Concurrent LoRA Adapters

1 code implementation6 Nov 2023 Ying Sheng, Shiyi Cao, Dacheng Li, Coleman Hooper, Nicholas Lee, Shuo Yang, Christopher Chou, Banghua Zhu, Lianmin Zheng, Kurt Keutzer, Joseph E. Gonzalez, Ion Stoica

To capitalize on these opportunities, we present S-LoRA, a system designed for the scalable serving of many LoRA adapters.

DISTFLASHATTN: Distributed Memory-efficient Attention for Long-context LLMs Training

1 code implementation5 Oct 2023 Dacheng Li, Rulin Shao, Anze Xie, Eric P. Xing, Xuezhe Ma, Ion Stoica, Joseph E. Gonzalez, Hao Zhang

FlashAttention (Dao, 2023) effectively reduces the quadratic peak memory usage to linear in training transformer-based large language models (LLMs) on a single GPU.

Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena

5 code implementations NeurIPS 2023 Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric P. Xing, Hao Zhang, Joseph E. Gonzalez, Ion Stoica

Evaluating large language model (LLM) based chat assistants is challenging due to their broad capabilities and the inadequacy of existing benchmarks in measuring human preferences.

Chatbot Language Modelling +2

Does compressing activations help model parallel training?

no code implementations6 Jan 2023 Song Bian, Dacheng Li, Hongyi Wang, Eric P. Xing, Shivaram Venkataraman

Finally, we provide insights for future development of model parallelism compression algorithms.

Quantization

MPCFormer: fast, performant and private Transformer inference with MPC

1 code implementation2 Nov 2022 Dacheng Li, Rulin Shao, Hongyi Wang, Han Guo, Eric P. Xing, Hao Zhang

Through extensive evaluations, we show that MPCFORMER significantly speeds up Transformer inference in MPC settings while achieving similar ML performance to the input model.

Knowledge Distillation

AMP: Automatically Finding Model Parallel Strategies with Heterogeneity Awareness

1 code implementation13 Oct 2022 Dacheng Li, Hongyi Wang, Eric Xing, Hao Zhang

Scaling up model sizes can lead to fundamentally new capabilities in many machine learning (ML) tasks.

valid

Dual Contradistinctive Generative Autoencoder

no code implementations CVPR 2021 Gaurav Parmar, Dacheng Li, Kwonjoon Lee, Zhuowen Tu

Our model, named dual contradistinctive generative autoencoder (DC-VAE), integrates an instance-level discriminative loss (maintaining the instance-level fidelity for the reconstruction/synthesis) with a set-level adversarial loss (encouraging the set-level fidelity for there construction/synthesis), both being contradistinctive.

Image Generation Image Reconstruction +1

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