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how_to_optimize_in_gpu- icon how_to_optimize_in_gpu-

This is a series of GPU optimization topics. Here we will introduce how to optimize the CUDA kernel in detail. I will introduce several basic kernel optimizations, including: elementwise, reduce, sgemv, sgemm, etc. The performance of these kernels is basically at or near the theoretical limit.

orb_slam2- icon orb_slam2-

Real-Time SLAM for Monocular, Stereo and RGB-D Cameras, with Loop Detection and Relocalization Capabilities

pcl-learning icon pcl-learning

🚀🚀🚀🚀PCL(Point Cloud Library)点云库学习记录

pytorch-mnist-celeba-gan-dcgan icon pytorch-mnist-celeba-gan-dcgan

Pytorch implementation of Generative Adversarial Networks (GAN) and Deep Convolutional Generative Adversarial Networks (DCGAN) for MNIST and CelebA datasets

stereoalgorithms- icon stereoalgorithms-

Stereo Algorithms (Include:CREStereo,RAFT-Stereo,Hitnet,FastACVNet_plus,Stereo Transformers,RealtimeStereo,DistDepth) with TensorRT,ORT,OpenVINO

tensorrt icon tensorrt

NVIDIA® TensorRT™ is an SDK for high-performance deep learning inference on NVIDIA GPUs. This repository contains the open source components of TensorRT.

tensorrt_starter icon tensorrt_starter

This repository give a guidline to learn CUDA and TensorRT from the beginning.

yolov5xxx icon yolov5xxx

YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

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