quettabit / convolution_kernelLinks
Accelerating CNN's convolution operation on GPUs by using memory-efficient data access patterns.
☆14Updated 7 years ago
Alternatives and similar repositories for convolution_kernel
Users that are interested in convolution_kernel are comparing it to the libraries listed below
Sorting:
- Test winograd convolution written in TVM for CUDA and AMDGPU☆41Updated 6 years ago
- Chameleon: Adaptive Code Optimization for Expedited Deep Neural Network Compilation☆27Updated 5 years ago
- Benchmark scripts for TVM☆74Updated 3 years ago
- ICML2017 MEC: Memory-efficient Convolution for Deep Neural Network C++实现(非官方)☆17Updated 6 years ago
- ☆69Updated 2 years ago
- Yet another Polyhedra Compiler for DeepLearning☆19Updated 2 years ago
- This is the implementation for paper: AdaTune: Adaptive Tensor Program CompilationMade Efficient (NeurIPS 2020).☆13Updated 4 years ago
- ☆36Updated 6 years ago
- Example for applying Gaussian and Laplace clipping on activations of CNN.☆34Updated 6 years ago
- GPU implementation of Winograd convolution☆10Updated 7 years ago
- This repository containts the pytorch scripts to train mixed-precision networks for microcontroller deployment, based on the memory contr…☆49Updated last year
- This is a PyTorch implementation of the Scalpel. Node pruning for five benchmark networks and SIMD-aware weight pruning for LeNet-300-100…☆41Updated 6 years ago
- Post-training sparsity-aware quantization☆34Updated 2 years ago
- source code of the paper: Robust Quantization: One Model to Rule Them All☆40Updated 2 years ago
- Benchmark of TVM quantized model on CUDA☆111Updated 4 years ago
- DNN quantization with outlier channel splitting☆112Updated 5 years ago
- GEMM and Winograd based convolutions using CUTLASS☆26Updated 4 years ago
- implementation of winograd minimal convolution algorithm on Intel Architecture☆39Updated 7 years ago
- Sandbox for TVM and playing around!☆22Updated 2 years ago
- ☆56Updated 4 years ago
- I'm going to use the Winograd’s minimal filtering algorithms to introduce a new class of fast algorithms for convolutional neural networks…☆12Updated 7 years ago
- TVM stack: exploring the incredible explosion of deep-learning frameworks and how to bring them together☆64Updated 7 years ago
- Official implementation of "Searching for Winograd-aware Quantized Networks" (MLSys'20)☆27Updated last year
- Repository containing pruned models and related information☆37Updated 4 years ago
- Benchmark for matrix multiplications between dense and block sparse (BSR) matrix in TVM, blocksparse (Gray et al.) and cuSparse.☆24Updated 4 years ago
- All about acceleration and compression of Deep Neural Networks☆33Updated 5 years ago
- PyTorch -> ONNX -> TVM for autotuning☆24Updated 5 years ago
- Code for our paper at ECCV 2020: Post-Training Piecewise Linear Quantization for Deep Neural Networks☆69Updated 3 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
- [CVPR'20] ZeroQ Mixed-Precision implementation (unofficial): A Novel Zero Shot Quantization Framework☆13Updated 4 years ago