42 citations · 49 across the 4 of their papers we have counts for
4 papers
TENET: A Framework for Modeling Tensor Dataflow Based on Relation-centric Notation
Liqiang Lu, Naiqing Guan, Yuyue Wang +5
Accelerating tensor applications on spatial architectures provides high performance and energy-efficiency, but requires accurate performance models for evaluating various dataflow…
HASCO: Towards Agile HArdware and Software CO-design for Tensor Computation
Qingcheng Xiao, Size Zheng, Bingzhe Wu +3
Tensor computations overwhelm traditional general-purpose computing devices due to the large amounts of data and operations of the computations. They call for a holistic solution c…
TensorLib: A Spatial Accelerator Generation Framework for Tensor Algebra
Liancheng Jia, Zizhang Luo, Liqiang Lu +1
Tensor algebra finds applications in various domains, and these applications, especially when accelerated on spatial hardware accelerators, can deliver high performance and low pow…
A Unified Framework of DNN Weight Pruning and Weight Clustering/Quantization Using ADMM
Shaokai Ye, Tianyun Zhang, Kaiqi Zhang +6
Many model compression techniques of Deep Neural Networks (DNNs) have been investigated, including weight pruning, weight clustering and quantization, etc. Weight pruning leverages…