Add functions for resource binding verification to librrun#972
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rapids-bot[bot] merged 21 commits intorapidsai:mainfrom Apr 17, 2026
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pentschev
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madsbk
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Apr 17, 2026
pentschev
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Apr 17, 2026
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| /** | ||
| * @brief Obtain the expected binding for a GPU from pre-discovered topology. | ||
| * | ||
| * Looks up @p gpu_id in @p topology and returns the expected CPU affinity, | ||
| * memory binding, and network devices. | ||
| * | ||
| * @param topology Pre-discovered system topology. | ||
| * @param gpu_id GPU device index to look up. | ||
| * @return The expected binding, or `std::nullopt` if @p gpu_id is not found. | ||
| */ | ||
| std::optional<expected_binding> get_expected_binding( | ||
| cucascade::memory::system_topology_info const& topology, int gpu_id | ||
| ); |
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This is currently not exposed to Python because cuCascade has no Python bindings. If we find a proper use case for this we can review this decision and add bindings ourselves.
madsbk
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Apr 17, 2026
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Thanks Mads! |
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/merge |
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RapidsMPF currently includes a CLI tool
check_resource_bindingfor live detection of hardware resource bindings. This functionality can also be useful as a library so that other projects can programmatically retrieve the information, thus move the implementation tolibrrunand adapt the tool to reuse that.Additionally, make optional use of that verification in
bind()functions, to strengthen resource binding confidence.