● Covered by 1 source · 1 reportLow impact1 neutral
TurboGPT: CUDA C++ Transformer Training Achieves 22KiB Model in 13 Seconds
Key points
- TurboGPT trains a 22KiB transformer in 13 seconds.
- Implemented in CUDA C++ with an MIT license.
- Supports Windows, Visual Studio 2022, and CUDA 13.4.
- Generates TensorBoard-compatible logs and checkpoints.
Fast Transformer Training
TurboGPT is a new tool that enables the training of a 22KiB transformer model in 13 seconds. This performance is achieved through its implementation in CUDA C++.
Technical Specifications and Environment
The tool is designed for byte-level GPT training and operates on Windows systems. It requires Visual Studio 2022 C++ tools and CUDA 13.4. Users specify the GPU compute capability using the CudaArch parameter during the build process.
Logging and Checkpointing Features
TurboGPT generates TensorBoard-compatible logs, with one report per batch, capped at 8Mi reports. These logs are flushed with periodic or final checkpoints. Training runs store checkpoints containing the model, optimizer, scheduler, and trainer state, allowing for resumed training using the --load option.
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Primary sources
GitHub cmc_internal/api GitHub github/collect GitHub lostmsu/TurboGPT GitHub _private/browser GitHub get-started/accessibility GitHub open-source/sponsorsReporting from
TurboGPT, a new CUDA C++ implementation, trains a 22KiB transformer model in 13 seconds. This tool allows for byte-level GPT training on Windows with Visual Studio 2022 and CUDA 13.4, offering fast iteration for small models.