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09/19/2023
GPT4AIGChip: Towards Next-Generation AI Accelerator Design Automation via Large Language Models
The remarkable capabilities and intricate nature of Artificial Intellige...
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05/09/2023
Instant-NeRF: Instant On-Device Neural Radiance Field Training via Algorithm-Accelerator Co-Designed Near-Memory Processing
Instant on-device Neural Radiance Fields (NeRFs) are in growing demand f...
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04/24/2023
Instant-3D: Instant Neural Radiance Field Training Towards On-Device AR/VR 3D Reconstruction
Neural Radiance Field (NeRF) based 3D reconstruction is highly desirable...
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03/19/2023
ERSAM: Neural Architecture Search For Energy-Efficient and Real-Time Social Ambiance Measurement
Social ambiance describes the context in which social interactions happe...
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12/05/2022
INGeo: Accelerating Instant Neural Scene Reconstruction with Noisy Geometry Priors
We present a method that accelerates reconstruction of 3D scenes and obj...
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12/02/2022
RT-NeRF: Real-Time On-Device Neural Radiance Fields Towards Immersive AR/VR Rendering
Neural Radiance Field (NeRF) based rendering has attracted growing atten...
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11/09/2022
ViTALiTy: Unifying Low-rank and Sparse Approximation for Vision Transformer Acceleration with a Linear Taylor Attention
Vision Transformer (ViT) has emerged as a competitive alternative to con...
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10/18/2022
ViTCoD: Vision Transformer Acceleration via Dedicated Algorithm and Accelerator Co-Design
Vision Transformers (ViTs) have achieved state-of-the-art performance on...
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06/15/2022
i-FlatCam: A 253 FPS, 91.49 μJ/Frame Ultra-Compact Intelligent Lensless Camera for Real-Time and Efficient Eye Tracking in VR/AR
We present a first-of-its-kind ultra-compact intelligent camera system, ...
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06/02/2022
EyeCoD: Eye Tracking System Acceleration via FlatCam-based Algorithm Accelerator Co-Design
Eye tracking has become an essential human-machine interaction modality ...
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12/21/2021
MIA-Former: Efficient and Robust Vision Transformers via Multi-grained Input-Adaptation
ViTs are often too computationally expensive to be fitted onto real-worl...
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11/19/2021
FBNetV5: Neural Architecture Search for Multiple Tasks in One Run
Neural Architecture Search (NAS) has been widely adopted to design accur...
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09/11/2021
2-in-1 Accelerator: Enabling Random Precision Switch for Winning Both Adversarial Robustness and Efficiency
The recent breakthroughs of deep neural networks (DNNs) and the advent o...
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07/16/2021
DANCE: DAta-Network Co-optimization for Efficient Segmentation Model Training and Inference
Semantic segmentation for scene understanding is nowadays widely demande...
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06/11/2021
A3C-S: Automated Agent Accelerator Co-Search towards Efficient Deep Reinforcement Learning
Driven by the explosive interest in applying deep reinforcement learning...
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04/22/2021
InstantNet: Automated Generation and Deployment of Instantaneously Switchable-Precision Networks
The promise of Deep Neural Network (DNN) powered Internet of Thing (IoT)...
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03/19/2021
HW-NAS-Bench:Hardware-Aware Neural Architecture Search Benchmark
HardWare-aware Neural Architecture Search (HW-NAS) has recently gained t...
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01/04/2021
SmartDeal: Re-Modeling Deep Network Weights for Efficient Inference and Training
The record-breaking performance of deep neural networks (DNNs) comes wit...
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12/24/2020
FracTrain: Fractionally Squeezing Bit Savings Both Temporally and Spatially for Efficient DNN Training
Recent breakthroughs in deep neural networks (DNNs) have fueled a tremen...
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10/28/2020
DNA: Differentiable Network-Accelerator Co-Search
Powerful yet complex deep neural networks (DNNs) have fueled a booming d...
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10/24/2020
ShiftAddNet: A Hardware-Inspired Deep Network
Multiplication (e.g., convolution) is arguably a cornerstone of modern d...
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05/07/2020
SmartExchange: Trading Higher-cost Memory Storage/Access for Lower-cost Computation
We present SmartExchange, an algorithm-hardware co-design framework to t...
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03/02/2020
A New MRAM-based Process In-Memory Accelerator for Efficient Neural Network Training with Floating Point Precision
The excellent performance of modern deep neural networks (DNNs) comes at...
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02/26/2020
DNN-Chip Predictor: An Analytical Performance Predictor for DNN Accelerators with Various Dataflows and Hardware Architectures
The recent breakthroughs in deep neural networks (DNNs) have spurred a t...
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01/06/2020
AutoDNNchip: An Automated DNN Chip Predictor and Builder for Both FPGAs and ASICs
Recent breakthroughs in Deep Neural Networks (DNNs) have fueled a growin...
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09/26/2019
