no code implementations • 27 Mar 2024 • Yuxiang Zhao, Zhuomin Chai, Xun Jiang, Yibo Lin, Runsheng Wang, Ru Huang
We are the first work to apply graph structure to deep-learning based dynamic IR drop prediction method.
no code implementations • 21 Feb 2024 • Shuzhang Zhong, Zebin Yang, Meng Li, Ruihao Gong, Runsheng Wang, Ru Huang
Additionally, it introduces a dynamic token tree generation algorithm to balance the computation and parallelism of the verification phase in real-time and maximize the overall efficiency across different batch sizes, sequence lengths, and tasks, etc.
no code implementations • 20 Feb 2024 • Tong Xie, Yixuan Hu, Renjie Wei, Meng Li, YuAn Wang, Runsheng Wang, Ru Huang
To overcome the compatibility challenges, ASCEND proposes a novel deterministic SC block for GELU and leverages an SC-friendly iterative approximate algorithm to design an accurate and efficient softmax circuit.
no code implementations • 29 Jan 2024 • Tianshi Xu, Meng Li, Runsheng Wang
Compared with prior-art HE-based protocols, e. g., CrypTFlow2, Cheetah, Iron, etc, HEQuant achieves $3. 5\sim 23. 4\times$ communication reduction and $3. 0\sim 9. 3\times$ latency reduction.
no code implementations • 26 Aug 2023 • Shuzhang Zhong, Meng Li, Yun Liang, Runsheng Wang, Ru Huang
Memory-aware network scheduling is becoming increasingly important for deep neural network (DNN) inference on resource-constrained devices.
no code implementations • 25 Aug 2023 • Tianshi Xu, Meng Li, Runsheng Wang, Ru Huang
Efficient networks, e. g., MobileNetV2, EfficientNet, etc, achieves state-of-the-art (SOTA) accuracy with lightweight computation.
no code implementations • 7 May 2023 • Yuxiang Zhao, Zhuomin Chai, Yibo Lin, Runsheng Wang, Ru Huang
Accurate early congestion prediction can prevent unpleasant surprises at the routing stage, playing a crucial character in assisting designers to iterate faster in VLSI design cycles.
no code implementations • 22 Mar 2023 • Renjie Wei, Shuwen Zhang, Zechun Liu, Meng Li, Yuchen Fan, Runsheng Wang, Ru Huang
While the performance of deep convolutional neural networks for image super-resolution (SR) has improved significantly, the rapid increase of memory and computation requirements hinders their deployment on resource-constrained devices.
1 code implementation • ICCV 2023 • Wenxuan Zeng, Meng Li, Wenjie Xiong, Tong Tong, Wen-jie Lu, Jin Tan, Runsheng Wang, Ru Huang
Secure multi-party computation (MPC) enables computation directly on encrypted data and protects both data and model privacy in deep learning inference.
no code implementations • 1 Aug 2022 • Zhuomin Chai, Yuxiang Zhao, Yibo Lin, Wei Liu, Runsheng Wang, Ru Huang
The electronic design automation (EDA) community has been actively exploring machine learning (ML) for very large-scale integrated computer-aided design (VLSI CAD).
no code implementations • 31 May 2020 • Qinggang Zhou, Yawen Zhang, Pengcheng Li, Xiaoyong Liu, Jun Yang, Runsheng Wang, Ru Huang
The state-of-the-art deep learning algorithms rely on distributed training systems to tackle the increasing sizes of models and training data sets.