Show HN: TurboGPT: train 22KiB transformer in 13s (github.com)

A new project named TurboGPT has been introduced, showcasing a remarkably efficient method for training a 22KiB transformer model in just 13 seconds using CUDA C++. Developed as part of MIT research, TurboGPT is built to run on Windows with Visual Studio 2022 and CUDA 13.4, making high-performance training more accessible for developers working with AI models. The project includes a streamlined process for model creation, utilizing a straightforward command-line interface to manage data, logging, and checkpointing. This development is significant for the AI/ML community as it emphasizes the potential for rapid training cycles and efficient resource utilization, paving the way for experimentation with very small models at a fraction of the traditional time and computational cost. TurboGPT can execute training on a specified dataset, recording detailed logs compatible with TensorBoard, allowing researchers to monitor performance metrics effectively. The system’s architecture supports resumption from checkpoints, ensuring flexibility in training workflows. Overall, TurboGPT represents a noteworthy advancement in model efficiency and could inspire new approaches to transformer training in constrained environments.