108 citations · 234 across the 37 of their papers we have counts for
10 papers · 1 filter
AutoWS: Automate Weights Streaming in Layer-wise Pipelined DNN Accelerators
Zhewen Yu, Christos-Savvas Bouganis
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 explore…
SATAY: A Streaming Architecture Toolflow for Accelerating YOLO Models on FPGA Devices
Alexander Montgomerie-Corcoran, Petros Toupas, Zhewen Yu +1
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 medi…
PASS: Exploiting Post-Activation Sparsity in Streaming Architectures for CNN Acceleration
Alexander Montgomerie-Corcoran, Zhewen Yu, Jianyi Cheng +1
With the ever-growing popularity of Artificial Intelligence, there is an increasing demand for more performant and efficient underlying hardware. Convolutional Neural Networks (CNN…
A Dataflow Compiler for Efficient LLM Inference using Custom Microscaling Formats
Jianyi Cheng, Cheng Zhang, Zhewen Yu +3
Model quantization represents both parameters (weights) and intermediate values (activations) in a more compact format, thereby directly reducing both computational and memory cost…
Mixed-TD: Efficient Neural Network Accelerator with Layer-Specific Tensor Decomposition
Zhewen Yu, Christos-Savvas Bouganis
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…
fpgaHART: A toolflow for throughput-oriented acceleration of 3D CNNs for HAR onto FPGAs
Petros Toupas, Christos-Savvas Bouganis, Dimitrios Tzovaras
Surveillance systems, autonomous vehicles, human monitoring systems, and video retrieval are just few of the many applications in which 3D Convolutional Neural Networks are exploit…
FMM-X3D: FPGA-based modeling and mapping of X3D for Human Action Recognition
Petros Toupas, Christos-Savvas Bouganis, Dimitrios Tzovaras
3D Convolutional Neural Networks are gaining increasing attention from researchers and practitioners and have found applications in many domains, such as surveillance systems, auto…
ATHEENA: A Toolflow for Hardware Early-Exit Network Automation
Benjamin Biggs, Christos-Savvas Bouganis, George A. Constantinides
The continued need for improvements in accuracy, throughput, and efficiency of Deep Neural Networks has resulted in a multitude of methods that make the most of custom architecture…
HARFLOW3D: A Latency-Oriented 3D-CNN Accelerator Toolflow for HAR on FPGA Devices
Petros Toupas, Alexander Montgomerie-Corcoran, Christos-Savvas Bouganis +1
For Human Action Recognition tasks (HAR), 3D Convolutional Neural Networks have proven to be highly effective, achieving state-of-the-art results. This study introduces a novel str…
Window-Based Early-Exit Cascades for Uncertainty Estimation: When Deep Ensembles are More Efficient than Single Models
Guoxuan Xia, Christos-Savvas Bouganis
Deep Ensembles are a simple, reliable, and effective method of improving both the predictive performance and uncertainty estimates of deep learning approaches. However, they are wi…