Lightweight encapsulated WebGPU rendering system example<9>-Basic lighting (source code)

Current sample source code github address: https://github.com/vilyLei/voxwebgpu/blob/main/src/voxgpu/sample/SimpleLightTest.ts Features implemented by this sample rendering system: 1. Isolation of user state and system state. For details, please see: Engine System Design Ideas – Isolation of User State and System State – CSDN Blog 2. Isolate high-frequency calls from low-frequency calls. 3. User-oriented ease of use packaging. 4. […]

YOLO lightweight improvement, edge GPU friendly YOLO improvement algorithm!

In this paper, the authors propose a new edge GPU-friendly module for multi-scale feature interaction based on the problem of missing combinatorial connections between various feature scales in existing advanced methods. In addition, the authors propose a new transfer learning backbone that is inspired by changes in the transformation information flow of different tasks, aiming […]

redroid11 integrated nvidia gpu hals

Foreword In this article, nvidia related aosp library and 510.155_Android_R_aarch64_release file are used to provide basic information from the original factory, which can be used for the basic ideas of aosp transplant library. This article records the practice of integrating nvidia gpu driver library and nvidia_omx driver library in redroid11 (aosp11) for memo. 1>. Apply […]

Pitfalls and solutions encountered when using GPU to train paddleocr model on new ubuntu

Directory 1. My ubuntu version! [Insert image description here](https://img-blog.csdnimg.cn/297945917309494ab03b50764e6fb775.png) 2. First pull the paddleocr source code 3. Download the model 4. Preparation before training 1. Create a file in the source code folder to put your own things 2. Prepare data 2.1 Data annotation 2.2 Data division 3. Rewrite the yml configuration file 4.Install anaconda […]

Ubuntu22.04 local deployment of PaddleSpeech experimental code (GPU version)

Foreword I have previously done a project related to the local deployment of PaddleSpeech experimental code (CPU version) on Ubuntu 18.04.6. Because it is the CPU version, the time-consuming aspects of synthesis/training are really impressive. With the previous experience, I deployed another The GPU version, to be honest, although it takes a lot less time […]

Use Hengyuan Cloud to rent a GPU server in the cloud to train the YOLOv8 model (including Linux system command explanation)

When it comes to deep learning training tasks, the computing power of GPU is indispensable. Compared with traditional central processing units (CPUs), graphics processing units (GPUs) have more powerful parallel computing capabilities and can significantly accelerate the training process of deep learning models. Deep learning algorithms usually involve a large number of matrix operations and […]

Solve The NVIDIA driver on your system is too old (found version 9010). Please update your GPU driver

Table of Contents Solve “The NVIDIA driver on your system is too old (found version 9010). Please update your GPU driver” 1. Check driver version 2. Download the latest NVIDIA driver 3. Uninstall old NVIDIA drivers 4. Install new NVIDIA driver 5. Verify that the new driver is installed successfully in conclusion Sample code: Check […]

2. The fabric based on pytorch lightning implements pytorch’s multi-GPU training and mixed precision functions

Article directory Undertake In the previous article, we used original pytorch to implement multi-GPU training and mixed precision. Now comparing the above code, we use Fabric to achieve the same function. Regarding Fabric, I will continue to explain it in subsequent blogs. It is explaining and learning. Through fabric, you can reduce the amount of […]