Search Results for author:
Found 4 papers, 0 papers with code
Tight Compression: Compressing CNN Through Fine-Grained Pruning and Weight Permutation for Efficient Implementation
Through permutation, the optimal arrangement of the weight matrix is obtained, and the sparse weight matrix is further compressed to a small and dense format to make full use of the hardware resources.
Accelerating Large Kernel Convolutions with Nested Winograd Transformation.pdf
This work proposes a nested Winograd algorithm that iteratively decomposes a large kernel convolution into small kernel convolutions and proves it to be more effective than the linear decomposition Winograd transformation algorithm.
A Comparison of the Taguchi Method and Evolutionary Optimization in Multivariate Testing
Its performance is compared to that of the Taguchi method in several simulated conditions, including an orthogonal one designed to favor the Taguchi method, and two realistic conditions with dependences between variables.
SparseNN: An Energy-Efficient Neural Network Accelerator Exploiting Input and Output Sparsity
Furthermore, an energy-efficient hardware architecture, SparseNN, is proposed to exploit both the input and output sparsity.
