1 citations · 1 across the 5 of their papers we have counts for
5 papers
IOPS: An Unified SpMM Accelerator Based on Inner-Outer-Hybrid Product
Wenhao Sun, Wendi Sun, Song Chen +1
Sparse matrix multiplication (SpMM) is widely applied to numerous domains, such as graph processing, machine learning, and data analytics. However, inner product based SpMM induces…
Bit-balance: Model-Hardware Co-design for Accelerating NNs by Exploiting Bit-level Sparsity
Wenhao Sun, Zhiwei Zou, Deng Liu +3
Bit-serial architectures can handle Neural Networks (NNs) with different weight precisions, achieving higher resource efficiency compared with bit-parallel architectures. Besides,…
Class-based Quantization for Neural Networks
Wenhao Sun, Grace Li Zhang, Huaxi Gu +2
In deep neural networks (DNNs), there are a huge number of weights and multiply-and-accumulate (MAC) operations. Accordingly, it is challenging to apply DNNs on resource-constraine…
SteppingNet: A Stepping Neural Network with Incremental Accuracy Enhancement
Wenhao Sun, Grace Li Zhang, Xunzhao Yin +4
Deep neural networks (DNNs) have successfully been applied in many fields in the past decades. However, the increasing number of multiply-and-accumulate (MAC) operations in DNNs pr…
Sense: Model Hardware Co-design for Accelerating Sparse CNN on Systolic Array
Wenhao Sun, Deng Liu, Zhiwei Zou +3
Sparsity is an intrinsic property of convolutional neural network(CNN) and worth exploiting for CNN accelerators, but extra processing comes with hardware overhead, causing many ar…