- 04 Nov, 2025 2 commits
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Daniel Hiltgen authored
* discovery: only retry AMD GPUs CUDA and Vulkan don't crash on unsupported devices, so retry isn't necessary. This also refactors the code to shift the Library specific logic into the ml package. * review comments
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Daniel Hiltgen authored
Also adjusts the vulkan windows build pattern to match recent changes in other backends so incremental builds are faster.
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- 31 Oct, 2025 1 commit
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Daniel Hiltgen authored
In CPU only setups the LibOllamaPath was omitted causing us not to load the ggml-cpu-XXX libraries during inference.
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- 28 Oct, 2025 1 commit
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Daniel Hiltgen authored
* Fix vulkan PCI ID and ID handling Intel GPUs may not report PCI IDs which was leading to incorrect overlap detection. Switch to using the existing PCI IDs, however AMD GPUs claim not to report PCI IDs, but actually do, so try anyway, as this is required for ADLX to find the GPUs on Windows. Numeric IDs lead to scheduling problems, so this also switches Vulkan to use UUID based IDs. The GPU discovery patches have been squashed into a single patch to simplify future rebases. * review comments
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- 23 Oct, 2025 1 commit
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Daniel Hiltgen authored
* DRY out the runner lifecycle code Now that discovery uses the runners as well, this unifies the runner spawning code into a single place. This also unifies GPU discovery types with the newer ml.DeviceInfo * win: make incremental builds better Place build artifacts in discrete directories so incremental builds don't have to start fresh * Adjust sort order to consider iGPUs * handle cpu inference oom scenarios * review comments
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- 01 Oct, 2025 1 commit
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Daniel Hiltgen authored
This revamps how we discover GPUs in the system by leveraging the Ollama runner. This should eliminate inconsistency between our GPU discovery and the runners capabilities at runtime, particularly for cases where we try to filter out unsupported GPUs. Now the runner does that implicitly based on the actual device list. In some cases free VRAM reporting can be unreliable which can leaad to scheduling mistakes, so this also includes a patch to leverage more reliable VRAM reporting libraries if available. Automatic workarounds have been removed as only one GPU leveraged this, which is now documented. This GPU will soon fall off the support matrix with the next ROCm bump. Additional cleanup of the scheduler and discovery packages can be done in the future once we have switched on the new memory management code, and removed support for the llama runner.
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