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Download README.md from ejschwartz/cuobjdump: direct link, hf CLI and curl.
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https://huggingface.co/spaces/ejschwartz/cuobjdump/resolve/main/README.md
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hf download hf://spaces/ejschwartz/cuobjdump/README.md
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686 Bytes
A newer version of the Gradio SDK is available: 6.31.0
metadata
title: cuobjdump / nvdisasm
emoji: 🔍
colorFrom: green
colorTo: gray
sdk: gradio
sdk_version: 6.29.1
app_file: app.py
pinned: false
short_description: Disassemble CUDA cubins with cuobjdump and nvdisasm
Upload a CUDA cubin, fatbin or ELF object and run NVIDIA's cuobjdump or nvdisasm on it.
Both tools are installed from PyPI (nvidia-cuda-cuobjdump, nvidia-cuda-nvdisasm); no GPU required.
nvdisasm 13.x cannot build control flow graphs for old-format CUDA ELF (pre-CUDA 13, OSABI 0x33), so those files are
routed to nvdisasm 12.9, downloaded from NVIDIA's redist site at startup.
examples/ holds two cubins assembled with ptxas from the included PTX sources.