A Low-Latency and Lightweight FPGA-Based Engine for Softmax and Layer Normalization Acceleration-Reference-Cited by-同舟云学术

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A Low-Latency and Lightweight FPGA-Based Engine for Softmax and Layer Normalization Acceleration

Published:2023-10-23 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Conference on Consumer Electronics-Asia (ICCE-Asia)
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Author:

Jeong Seongho¹,Seo Minseok¹,Nguyen Xuan Truong¹,Lee Hyuk-Jae¹

Affiliation:

1. Seoul National University,Department of Electrical and Computer Engineering

Funder

Technology Development

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10326218/10326328/10326397.pdf?arnumber=10326397

Reference7 articles.

1. ViT-P3DE∗: Vision Transformer Based Multi-Camera Instance Association with Pseudo 3D Position Embeddings

2. An image is worth 16x16 words: Transformers for image recognition at scale;dosovitskiy,2020

3. A Fast and Flexible FPGA-based Accelerator for Natural Language Processing Neural Networks

4. DFX: A Low-latency Multi-FPGA Appliance for Accelerating Transformer-based Text Generation

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Low-Latency and Scalable Vector Engine with Operation Fusion for Transformers;2024 IEEE 6th International Conference on AI Circuits and Systems (AICAS);2024-04-22

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