3 papers
cs.CV2025
FG-Attn: Leveraging Fine-Grained Sparse Attention in Video Diffusion Models
Sankeerth Durvasula, Kavya Sreedhar, Zain Moustafa +6
Using diffusion transformers for media generation may require evaluating attention over extremely long sequences, with attention layers accounting for the majority of generation la…
cs.AR2021
OCCAM: Optimal Data Reuse for Convolutional Neural Networks
Ashish Gondimalla, Jianqiao Liu, T. N. Vijaykumar +1
Convolutional neural networks (CNNs) are emerging as powerful tools for image processing in important commercial applications. We focus on the important problem of improving the la…
cs.AR2021
Barrier-Free Large-Scale Sparse Tensor Accelerator (BARISTA) For Convolutional Neural Networks
Ashish Gondimalla, Sree Charan Gundabolu, T. N. Vijaykumar +1
Convolutional neural networks (CNNs) are emerging as powerful tools for visual recognition. Recent architecture proposals for sparse CNNs exploit zeros in the feature maps and filt…