Shypd.aiThe largest open index of AI toolsunet.cu is an open-source Coding & Development tool that implements a UNet diffusion model in pure CUDA. It offers an alternative to PyTorch for training unconditional diffusion models, with performance benchmarks available.
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unet.cu is an open-source project that provides a UNet diffusion model implemented entirely in C++/CUDA. Inspired by Andrej Karpathy's llm.c, the goal is to achieve performance comparable to PyTorch implementations, specifically for training unconditional diffusion models. The repository includes benchmarks showing its training speed relative to PyTorch and PyTorch with `torch.compile`. It supports training with sample images from ImageNet 64x64 and allows users to train with their own data. The project emphasizes learning CUDA concepts and provides a detailed breakdown of its architecture, including custom convolution kernels and optimizations to avoid inefficient data transposes.
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