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20172026
most citedSCNN: An Accelerator for Compressed-sparse Convolutional Neural Networks

125 citations · 361 across the 45 of their papers we have counts for

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Showing 2022Show all

6 papers · 1 filter

cs.LG2022★ 1 cited

HEAT: Hardware-Efficient Automatic Tensor Decomposition for Transformer Compression

Jiaqi Gu, Ben Keller, Jean Kossaifi +3

Transformers have attained superior performance in natural language processing and computer vision. Their self-attention and feedforward layers are overparameterized, limiting infe…

cs.LG2022★ 2 cited

An Adversarial Active Sampling-based Data Augmentation Framework for Manufacturable Chip Design

Mingjie Liu, Haoyu Yang, Zongyi Li +7

Lithography modeling is a crucial problem in chip design to ensure a chip design mask is manufacturable. It requires rigorous simulations of optical and chemical models that are co…

cs.LG2022★ 3 cited

Large Scale Mask Optimization Via Convolutional Fourier Neural Operator and Litho-Guided Self Training

Haoyu Yang, Zongyi Li, Kumara Sastry +5

Machine learning techniques have been extensively studied for mask optimization problems, aiming at better mask printability, shorter turnaround time, better mask manufacturability…

cs.LG2022★ 11 cited

Optimal Clipping and Magnitude-aware Differentiation for Improved Quantization-aware Training

Charbel Sakr, Steve Dai, Rangharajan Venkatesan +3

Data clipping is crucial in reducing noise in quantization operations and improving the achievable accuracy of quantization-aware training (QAT). Current practices rely on heuristi…

cs.OH2022

Generic Lithography Modeling with Dual-band Optics-Inspired Neural Networks

Haoyu Yang, Zongyi Li, Kumara Sastry +6

Lithography simulation is a critical step in VLSI design and optimization for manufacturability. Existing solutions for highly accurate lithography simulation with rigorous models…

cs.LG2022★ 1 cited

GATSPI: GPU Accelerated Gate-Level Simulation for Power Improvement

Yanqing Zhang, Haoxing Ren, Akshay Sridharan +1

In this paper, we present GATSPI, a novel GPU accelerated logic gate simulator that enables ultra-fast power estimation for industry sized ASIC designs with millions of gates. GATS…