ARM-software / scalpel
This is a PyTorch implementation of the Scalpel. Node pruning for five benchmark networks and SIMD-aware weight pruning for LeNet-300-100 and LeNet-5 is included.
☆41Updated 6 years ago
Alternatives and similar repositories for scalpel:
Users that are interested in scalpel are comparing it to the libraries listed below
- Code for paper "SWALP: Stochastic Weight Averaging forLow-Precision Training".☆62Updated 5 years ago
- Test winograd convolution written in TVM for CUDA and AMDGPU☆40Updated 6 years ago
- Training neural networks with 8-bit computations☆28Updated 8 years ago
- This repository represents training examples for the CVPR 2018 paper "SYQ:Learning Symmetric Quantization For Efficient Deep Neural Netwo…☆31Updated 5 years ago
- ☆53Updated 7 years ago
- PyProf2: PyTorch Profiling tool☆82Updated 4 years ago
- Repository containing pruned models and related information☆37Updated 4 years ago
- ☆53Updated 6 years ago
- PyTorch implementation of Wide Residual Networks with 1-bit weights by McDonnell (ICLR 2018)☆124Updated 6 years ago
- Mayo: Auto-generation of hardware-friendly deep neural networks. Dynamic Channel Pruning: Feature Boosting and Suppression.☆114Updated 5 years ago
- Efficient forward propagation for BCNNs☆50Updated 7 years ago
- Simple Training and Deployment of Fast End-to-End Binary Networks☆158Updated 3 years ago
- Implementation of ICLR 2018 paper "Loss-aware Weight Quantization of Deep Networks"☆26Updated 5 years ago
- Training Low-bits DNNs with Stochastic Quantization☆73Updated 7 years ago
- ☆47Updated 5 years ago
- Implementation of Ternary Weight Networks In Caffe☆63Updated 8 years ago
- Code for paper "Energy-Constrained Compression for Deep Neural Networks via Weighted Sparse Projection and Layer Input Masking"☆17Updated 5 years ago
- A Unified, Systematic Framework of Structured Weight Pruning for DNNs☆22Updated 6 years ago
- A PyTorch implementation of the iterative pruning method described in Han et. al. (2015)☆40Updated 6 years ago
- Code example for the ICLR 2018 oral paper☆151Updated 6 years ago
- Implementation for the paper "Latent Weights Do Not Exist: Rethinking Binarized Neural Network Optimization"☆74Updated 5 years ago
- Class Project for 18663 - Implementation of FBNet (Hardware-Aware DNAS)☆34Updated 5 years ago
- Deep learning with a multiplication budget☆47Updated 6 years ago
- Code for BlockSwap (ICLR 2020).☆33Updated 3 years ago
- Train neural networks with joint quantization and pruning on both weights and activations using any pytorch modules☆40Updated 2 years ago
- Reproduction of WAGE in PyTorch.☆41Updated 6 years ago
- DNN quantization with outlier channel splitting☆112Updated 4 years ago
- LCNN: Lookup-based Convolutional Neural Network☆52Updated 7 years ago
- Training wide residual networks for deployment using a single bit for each weight - Official Code Repository for ICLR 2018 Published Pape…☆36Updated 4 years ago
- A PyTorch implementation of "Incremental Network Quantization: Towards Lossless CNNs with Low-Precision Weights"☆167Updated 5 years ago