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08/30/2023
READ: Reliability-Enhanced Accelerator Dataflow Optimization using Critical Input Pattern Reduction
With the rapid advancements of deep learning in recent years, hardware a...
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08/26/2023
Memory-aware Scheduling for Complex Wired Networks with Iterative Graph Optimization
Memory-aware network scheduling is becoming increasingly important for d...
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08/25/2023
Falcon: Accelerating Homomorphically Encrypted Convolutions for Efficient Private Mobile Network Inference
Efficient networks, e.g., MobileNetV2, EfficientNet, etc, achieves state...
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07/16/2023
Probabilistic Compute-in-Memory Design For Efficient Markov Chain Monte Carlo Sampling
Markov chain Monte Carlo (MCMC) is a widely used sampling method in mode...
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07/15/2023
Reducing operator complexity in Algebraic Multigrid with Machine Learning Approaches
We propose a data-driven and machine-learning-based approach to compute ...
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05/07/2023
HybridNet: Dual-Branch Fusion of Geometrical and Topological Views for VLSI Congestion Prediction
Accurate early congestion prediction can prevent unpleasant surprises at...
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03/22/2023
EBSR: Enhanced Binary Neural Network for Image Super-Resolution
While the performance of deep convolutional neural networks for image su...
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11/25/2022
MPCViT: Searching for MPC-friendly Vision Transformer with Heterogeneous Attention
Secure multi-party computation (MPC) enables computation directly on enc...
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11/07/2022
Extremely-Fast, Energy-Efficient Massive MIMO Precoding with Analog RRAM Matrix Computing
Signal processing in wireless communications, such as precoding, detecti...
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08/01/2022
CircuitNet: An Open-Source Dataset for Machine Learning Applications in Electronic Design Automation (EDA)
The electronic design automation (EDA) community has been actively explo...
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02/24/2021
Learning optimal multigrid smoothers via neural networks
Multigrid methods are one of the most efficient techniques for solving l...
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01/23/2021
Generating a Doppelganger Graph: Resembling but Distinct
Deep generative models, since their inception, have become increasingly ...
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05/31/2020
DaSGD: Squeezing SGD Parallelization Performance in Distributed Training Using Delayed Averaging
The state-of-the-art deep learning algorithms rely on distributed traini...
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04/23/2019
New-Generation Design-Technology Co-Optimization (DTCO): Machine-Learning Assisted Modeling Framework
In this paper, we propose a machine-learning assisted modeling framework...
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04/21/2019
