Characterization of MPC-based Private Inference for Transformer-based Models-Reference-Cited by-同舟云学术

Characterization of MPC-based Private Inference for Transformer-based Models

Published:2022-05 Issue: Volume: Page:
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Container-title:2022 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)
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Author:

Wang Yongqin¹,Suh G. Edward²,Xiong Wenjie²,Lefaudeux Benjamin²,Knott Brian²,Annavaram Murali¹,Lee Hsien-Hsin S.²

Affiliation:

1. University of Southern California

2. Meta AI

Publisher

IEEE

Link

Reference33 articles.

1. TT-REC: Tensor train compression for deep learning recommendation model embeddings;yin;arXiv preprint arXiv 2101 10955,2021

2. Nyströmformer: A nyström-based algorithm for approximating self-attention;xiong;Association for the Advancement of Artificial Intelligence,2021

3. Linformer: Self-attention with linear complexity;wang;arXiv preprint arXiv 2006 04989,2020

4. FALCON: Honest-majority maliciously secure framework for private deep learning;wagh;Proceedings on Privacy Enhancing Technologies,2020

5. Gaussian error linear units (gelus);hendrycks,2020

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3. Characterizing and Optimizing End-to-End Systems for Private Inference;Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 3;2023-03-25