Hugging Face Blog
Visualize and understand GPU memory in PyTorch
Read the original on Hugging Face Blog →The Flow has not summarised this story yet — read it at Hugging Face Blog.
Related stories
Hugging Face Blog
May 29
Profiling in PyTorch (Part 1): A Beginner's Guide to torch.profiler
Hugging Face Blog
Jul 10
Profiling in PyTorch (Part 3): Attention is all you profile
arXiv Machine Learning
Jun 11
A Scalable PyTorch Abstraction for Multi-GPU Gaussian Splatting
arXiv:2606. 11390v1 Announce Type: cross Abstract: Gaussian splatting methods have become increasingly popular for neural reconstruction of the real world.
arXiv Computer Vision
Aug 26
TorchMorph: CUDA-accelerated Morphological Transforms
arXiv:2608.24738v1 Announce Type: new Abstract: Morphological transforms are long-standing tools for shape and mask processing, but the de facto reference implementation in the Python ecosystem, i.e....
Hugging Face Trending Papers
Aug 25
TorchMorph: CUDA-accelerated Morphological Transforms
Morphological transforms are long-standing tools for shape and mask processing, but the de facto reference implementation in the Python ecosystem, i.e. scipy.ndimage, is CPU-only, single-array, and th...
arXiv AI
Jul 21
KernelBench-Verified: Do LLM-Generated Kernels Actually Beat PyTorch?
arXiv:2607. 16241v1 Announce Type: cross Abstract: Recent large language models (LLMs) can generate custom CUDA kernels that appear to outperform PyTorch on benchmarks such as KernelBench.