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05/31/2023
Integrated multi-operand optical neurons for scalable and hardware-efficient deep learning
The optical neural network (ONN) is a promising hardware platform for ne...
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05/31/2023
DOTA: A Dynamically-Operated Photonic Tensor Core for Energy-Efficient Transformer Accelerator
The wide adoption and significant computing resource consumption of atte...
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05/31/2023
M3ICRO: Machine Learning-Enabled Compact Photonic Tensor Core based on PRogrammable Multi-Operand Multimode Interference
Photonic computing shows promise for transformative advancements in mach...
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05/24/2023
Pre-RMSNorm and Pre-CRMSNorm Transformers: Equivalent and Efficient Pre-LN Transformers
Transformers have achieved great success in machine learning application...
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11/30/2022
HEAT: Hardware-Efficient Automatic Tensor Decomposition for Transformer Compression
Transformers have attained superior performance in natural language proc...
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10/30/2022
QuEst: Graph Transformer for Quantum Circuit Reliability Estimation
Among different quantum algorithms, PQC for QML show promises on near-te...
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10/27/2022
An Adversarial Active Sampling-based Data Augmentation Framework for Manufacturable Chip Design
Lithography modeling is a crucial problem in chip design to ensure a chi...
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09/19/2022
NeurOLight: A Physics-Agnostic Neural Operator Enabling Parametric Photonic Device Simulation
Optical computing is an emerging technology for next-generation efficien...
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09/07/2022
TAG: Learning Circuit Spatial Embedding From Layouts
Analog and mixed-signal (AMS) circuit designs still rely on human design...
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08/17/2022
Fuse and Mix: MACAM-Enabled Analog Activation for Energy-Efficient Neural Acceleration
Analog computing has been recognized as a promising low-power alternativ...
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07/30/2022
Delving into Effective Gradient Matching for Dataset Condensation
As deep learning models and datasets rapidly scale up, network training ...
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02/26/2022
QOC: Quantum On-Chip Training with Parameter Shift and Gradient Pruning
Parameterized Quantum Circuits (PQC) are drawing increasing research int...
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12/15/2021
ELight: Enabling Efficient Photonic In-Memory Neurocomputing with Life Enhancement
With the recent advances in optical phase change material (PCM), photoni...
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11/11/2021
Silicon photonic subspace neural chip for hardware-efficient deep learning
As deep learning has shown revolutionary performance in many artificial ...
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11/01/2021
HRViT: Multi-Scale High-Resolution Vision Transformer
Vision transformers (ViTs) have attracted much attention for their super...
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10/27/2021
L2ight: Enabling On-Chip Learning for Optical Neural Networks via Efficient in-situ Subspace Optimization
Silicon-photonics-based optical neural network (ONN) is a promising hard...
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10/21/2021
RoQNN: Noise-Aware Training for Robust Quantum Neural Networks
Quantum Neural Network (QNN) is a promising application towards quantum ...
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10/04/2021
A New Acceleration Paradigm for Discrete CosineTransform and Other Fourier-Related Transforms
Discrete cosine transform (DCT) and other Fourier-related transforms hav...
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10/01/2021
DNN-Opt: An RL Inspired Optimization for Analog Circuit Sizing using Deep Neural Networks
Analog circuit sizing takes a significant amount of manual effort in a t...
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09/06/2021
Delving into Macro Placement with Reinforcement Learning
In physical design, human designers typically place macros via trial and...
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08/25/2021
Towards Memory-Efficient Neural Networks via Multi-Level in situ Generation
Deep neural networks (DNN) have shown superior performance in a variety ...
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07/22/2021
QuantumNAS: Noise-Adaptive Search for Robust Quantum Circuits
Quantum noise is the key challenge in Noisy Intermediate-Scale Quantum (...
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04/01/2021
Optimizer Fusion: Efficient Training with Better Locality and Parallelism
Machine learning frameworks adopt iterative optimizers to train neural n...
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12/21/2020
Efficient On-Chip Learning for Optical Neural Networks Through Power-Aware Sparse Zeroth-Order Optimization
Optical neural networks (ONNs) have demonstrated record-breaking potenti...
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03/02/2020
TimingCamouflage+: Netlist Security Enhancement with Unconventional Timing (with Appendix)
With recent advances in reverse engineering, attackers can reconstruct a...
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09/20/2018
OpenMPL: An Open Source Layout Decomposer
Multiple patterning lithography has been widely adopted in advanced tech...
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06/27/2018