Zobrazeno 1 - 10
of 207
pro vyhledávání: '"Bouganis, Christos"'
Autor:
Yu, Zhewen, Sreeram, Sudarshan, Agrawal, Krish, Wu, Junyi, Montgomerie-Corcoran, Alexander, Zhang, Cheng, Cheng, Jianyi, Bouganis, Christos-Savvas, Zhao, Yiren
Deep Neural Networks (DNNs) excel in learning hierarchical representations from raw data, such as images, audio, and text. To compute these DNN models with high performance and energy efficiency, these models are usually deployed onto customized hard
Externí odkaz:
http://arxiv.org/abs/2406.03088
Autor:
Chen, Pengtao, Shen, Mingzhu, Ye, Peng, Cao, Jianjian, Tu, Chongjun, Bouganis, Christos-Savvas, Zhao, Yiren, Chen, Tao
Diffusion models are widely recognized for generating high-quality and diverse images, but their poor real-time performance has led to numerous acceleration works, primarily focusing on UNet-based structures. With the more successful results achieved
Externí odkaz:
http://arxiv.org/abs/2406.01125
Convolutional Neural Networks (CNNs) have demonstrated their effectiveness in numerous vision tasks. However, their high processing requirements necessitate efficient hardware acceleration to meet the application's performance targets. In the space o
Externí odkaz:
http://arxiv.org/abs/2403.18921
Label smoothing (LS) is a popular regularisation method for training neural networks as it is effective in improving test accuracy and is simple to implement. Hard one-hot labels are smoothed by uniformly distributing probability mass to other classe
Externí odkaz:
http://arxiv.org/abs/2403.14715
Autor:
Yu, Zhewen, Bouganis, Christos-Savvas
With the great success of Deep Neural Networks (DNN), the design of efficient hardware accelerators has triggered wide interest in the research community. Existing research explores two architectural strategies: sequential layer execution and layer-w
Externí odkaz:
http://arxiv.org/abs/2311.04764
AI has led to significant advancements in computer vision and image processing tasks, enabling a wide range of applications in real-life scenarios, from autonomous vehicles to medical imaging. Many of those applications require efficient object detec
Externí odkaz:
http://arxiv.org/abs/2309.01587
Autor:
Cheng, Jianyi, Zhang, Cheng, Yu, Zhewen, Bouganis, Christos-Savvas, Constantinides, George A., Zhao, Yiren
Model quantization represents both parameters (weights) and intermediate values (activations) in a more compact format, thereby directly reducing both computational and memory cost in hardware. The quantization of recent large language models (LLMs)
Externí odkaz:
http://arxiv.org/abs/2307.15517
With the ever-growing popularity of Artificial Intelligence, there is an increasing demand for more performant and efficient underlying hardware. Convolutional Neural Networks (CNN) are a workload of particular importance, which achieve high accuracy
Externí odkaz:
http://arxiv.org/abs/2307.07821
Autor:
Yu, Zhewen, Bouganis, Christos-Savvas
Neural Network designs are quite diverse, from VGG-style to ResNet-style, and from Convolutional Neural Networks to Transformers. Towards the design of efficient accelerators, many works have adopted a dataflow-based, inter-layer pipelined architectu
Externí odkaz:
http://arxiv.org/abs/2306.05021