no code implementations • 17 Mar 2024 • Kaiyan Chang, Kun Wang, Nan Yang, Ying Wang, Dantong Jin, Wenlong Zhu, Zhirong Chen, Cangyuan Li, Hao Yan, Yunhao Zhou, Zhuoliang Zhao, Yuan Cheng, Yudong Pan, Yiqi Liu, Mengdi Wang, Shengwen Liang, Yinhe Han, Huawei Li, Xiaowei Li
Our 13B model (ChipGPT-FT) has a pass rate improvement compared with GPT-3. 5 in Verilog generation and outperforms in EDA script (i. e., SiliconCompiler) generation with only 200 EDA script data.
no code implementations • 23 May 2023 • Kaiyan Chang, Ying Wang, Haimeng Ren, Mengdi Wang, Shengwen Liang, Yinhe Han, Huawei Li, Xiaowei Li
As large language models (LLMs) like ChatGPT exhibited unprecedented machine intelligence, it also shows great performance in assisting hardware engineers to realize higher-efficiency logic design via natural language interaction.
1 code implementation • 30 Mar 2023 • Hanqi Jiang, Cheng Zeng, Runnan Chen, Shuai Liang, Yinhe Han, Yichao Gao, Conglin Wang
To address this problem, we propose a neural implicit surface learning method called Depth-NeuS based on depth information optimization for multi-view reconstruction.
1 code implementation • International Conference on Machine Learning 2022 • Zihao Sun, Yu Hu, Shun Lu, Longxing Yang, Jilin Mei, Yinhe Han, Xiaowei Li
We utilize the attention weights to represent the importance of the relevant operations for the micro search or the importance of the relevant blocks for the macro search.
no code implementations • 30 Jan 2022 • Weidong Cao, Yilong Zhao, Adith Boloor, Yinhe Han, Xuan Zhang, Li Jiang
This paper presents a new PIM architecture to efficiently accelerate deep learning tasks by minimizing the required A/D conversions with analog accumulation and neural approximated peripheral circuits.
1 code implementation • CVPR 2020 • Beibei Jin, Yu Hu, Qiankun Tang, Jingyu Niu, Zhiping Shi, Yinhe Han, Xiaowei Li
Inspired by the frequency band decomposition characteristic of Human Vision System (HVS), we propose a video prediction network based on multi-level wavelet analysis to deal with spatial and temporal information in a unified manner.
Ranked #1 on Video Prediction on KTH (PSNR metric)
no code implementations • 8 Nov 2019 • Xiaoming Chen, Yinhe Han, Yu Wang
Evaluations based on the 65nm technology demonstrate that the proposed architecture nearly reaches the theoretical minimum communication in a three-level memory hierarchy and it is computation dominant.
Distributed, Parallel, and Cluster Computing Hardware Architecture
1 code implementation • NeurIPS 2018 • Shice Liu, Yu Hu, Yiming Zeng, Qiankun Tang, Beibei Jin, Yinhe Han, Xiaowei Li
Semantic scene completion predicts volumetric occupancy and object category of a 3D scene, which helps intelligent agents to understand and interact with the surroundings.