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Efficient deployment of large language models (LLMs) necessitates low-bit quantization to minimize model size and inference cost.
Song Han, Huizi Mao, and William J Dally · 2015
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Fixed point quantization of deep convolutional networks
Darryl Lin, Sachin Talathi, and Sreekanth Annapureddy · 2016
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The wikitext long term dependency language modeling dataset
Stephen Merity · 2016
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The lambada dataset: Word prediction requiring a broad discourse context
Denis Paperno, Germán Kruszewski, Angeliki Lazaridou, Quan Ngoc Pham, Raffaella Bernardi, Sandro Pezzelle, Marco Baroni, Gemma Boleda, and Raquel Fernández · 2016
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Quantization and training of neural networks for efficient integer-arithmetic-only inference
Benoit Jacob, Skirmantas Kligys, Bo Chen, Menglong Zhu, Matthew Tang, Andrew Howard, Hartwig Adam, and Dmitry Kalenichenko · 2018
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Model compression via distillation and quantization
Antonio Polino, Razvan Pascanu, and Dan Alistarh · 2018
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Hybrid 8-bit floating point (hfp8) training and inference for deep neural networks
Xiao Sun, Jungwook Choi, Chia-Yu Chen, Naigang Wang, Swagath Venkataramani, Vijayalakshmi Viji Srinivasan, Xiaodong Cui, Wei Zhang, and Kailash Gopalakrishnan · 2019
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Hellaswag: Can a machine really finish your sentence?
Rowan Zellers, Ari Holtzman, Yonatan Bisk, Ali Farhadi, and Yejin Choi · 2019
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Piqa: Reasoning about physical commonsense in natural language
Yonatan Bisk, Rowan Zellers, Jianfeng Gao, Yejin Choi, et al · 2020
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Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
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Integer quantization for deep learning inference: Principles and empirical evaluation
Hao Wu, Patrick Judd, Xiaojie Zhang, Mikhail Isaev, and Paulius Micikevicius · 2020
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9.1 a 7nm 4-core ai chip with 25.6 tflops hybrid fp8 training, 102.4 tops int4 inference and workload-aware throttling
Ankur Agrawal, Sae Kyu Lee, Joel Silberman, Matthew Ziegler, Mingu Kang, Swagath Venkataramani, Nianzheng Cao, Bruce Fleischer, Michael Guillorn, Matthew Cohen, et al · 2021
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A survey of quantization methods for efficient neural network inference
Fp8 quantization: The power of the exponent
Andrey Kuzmin, Mart Van Baalen, Yuwei Ren, Markus Nagel, Jorn Peters, and Tijmen Blankevoort · 2022
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Paulius Micikevicius, Dusan Stosic, Neil Burgess, Marius Cornea, Pradeep Dubey, Richard Grisenthwaite, Sangwon Ha, Alexander Heinecke, Patrick Judd, John Kamalu, et al · 2022
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nuqmm: Quantized matmul for efficient inference of large-scale generative language models
Gunho Park, Baeseong Park, Se Jung Kwon, Byeongwook Kim, Youngjoo Lee, and Dongsoo Lee · 2022
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Smoothquant: Accurate and efficient post-training quantization for large language models
Guangxuan Xiao, Ji Lin, Mickael Seznec, Julien Demouth, and Song Han · 2022
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Amir Gholami, Sehoon Kim, Zhen Dong, Zhewei Yao, Michael W Mahoney, and Kurt Keutzer · 2021
Cited alongside, same era.
Llm. int8 (): 8-bit matrix multiplication for transformers at scale
Tim Dettmers, Mike Lewis, Younes Belkada, and Luke Zettlemoyer · 2022
Cited alongside, same era.
Gptq: Accurate post-training quantization for generative pre-trained transformers
Elias Frantar, Saleh Ashkboos, Torsten Hoefler, and Dan Alistarh · 2022
Cited alongside, same era.
https://github.com/IST-DASLab/gptq
GPTQ Library
Cited in the paper.
https://resources.nvidia.com/en-us-tensor-core
NVIDIA H100 Tensor Core GPU Architecture
Cited in the paper.
https://github.com/openppl-public/ppq
PPQ Library
Cited in the paper.
Zeroquant: Efficient and affordable post-training quantization for large-scale transformers
Zhewei Yao, Reza Yazdani Aminabadi, Minjia Zhang, Xiaoxia Wu, Conglong Li, and Yuxiong He · 2022
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Opt: Open pre-trained transformer language models
Susan Zhang, Stephen Roller, Naman Goyal, Mikel Artetxe, Moya Chen, Shuohui Chen, Christopher Dewan, Mona Diab, Xian Li, Xi Victoria Lin, et al · 2022
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Llama: Open and efficient foundation language models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, et al · 2023
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