Two comments inline. Other than that, please consider it:
Reviewed-by: Christoph Heiss <[email protected]> On Thu Mar 5, 2026 at 10:16 AM CET, Dominik Csapak wrote: [..] > diff --git a/pve-rs/Cargo.toml b/pve-rs/Cargo.toml > index 45389b5..3b6c2fc 100644 > --- a/pve-rs/Cargo.toml > +++ b/pve-rs/Cargo.toml > @@ -20,6 +20,7 @@ hex = "0.4" > http = "1" > libc = "0.2" > nix = "0.29" > +nvml-wrapper = "0.12" Missing the respective entry in d/control. [..] > diff --git a/pve-rs/src/bindings/nvml.rs b/pve-rs/src/bindings/nvml.rs > new file mode 100644 > index 0000000..0f4c81e > --- /dev/null > +++ b/pve-rs/src/bindings/nvml.rs > @@ -0,0 +1,91 @@ > +//! Provides access to the state of NVIDIA (v)GPU devices connected to the > system. > + > +#[perlmod::package(name = "PVE::RS::NVML", lib = "pve_rs")] > +pub mod pve_rs_nvml { > + //! The `PVE::RS::NVML` package. > + //! > + //! Provides high level helpers to get info from the system with NVML. > + > + use anyhow::Result; > + use nvml_wrapper::Nvml; > + use perlmod::Value; > + > + /// Retrieves a list of *creatable* vGPU types for the specified GPU by > bus id. > + /// > + /// The [`bus_id`] is of format > "\<domain\>:\<bus\>:\<device\>.\<function\>", > + /// e.g. "0000:01:01.0". > + /// > + /// # See also > + /// > + /// [`nvmlDeviceGetCreatableVgpus`]: > <https://docs.nvidia.com/deploy/nvml-api/group__nvmlVgpu.html#group__nvmlVgpu_1ge86fff933c262740f7a374973c4747b6> > + /// [`nvmlDeviceGetHandleByPciBusId_v2`]: > <https://docs.nvidia.com/deploy/nvml-api/group__nvmlDeviceQueries.html#group__nvmlDeviceQueries_1gea7484bb9eac412c28e8a73842254c05> > + /// [`struct nvmlPciInfo_t`]: > <https://docs.nvidia.com/deploy/nvml-api/structnvmlPciInfo__t.html#structnvmlPciInfo__t_1a4d54ad9b596d7cab96ecc34613adbe4> > + #[export] > + fn creatable_vgpu_types_for_dev(bus_id: &str) -> Result<Vec<Value>> { > + let nvml = Nvml::init()?; Looking at this, I was wondering how expensive that call is, considering this path is triggered from the API. Same for supported_vgpu_types_for_dev() below. Did some quick & simple benchmarking - on average, `Nvml::init()` took ~32ms, with quite some variance; at best ~26ms up to an worst case of >150ms. IMO nothing worth blocking the series on, as this falls into premature optimization territory and can be fixed in the future, if needed. Holding an instance in memory might also be problematic on driver upgrades? I.e. we keep an old version of the library loaded, and thus mismatched API. The above results were done with one GPU only though, so potentially could be worse on multi-GPU systems. > + let device = nvml.device_by_pci_bus_id(bus_id)?; > + > + build_vgpu_type_list(device.vgpu_creatable_types()?) > + } > + > + /// Retrieves a list of *supported* vGPU types for the specified GPU by > bus id. > + /// > + /// The [`bus_id`] is of format > "\<domain\>:\<bus\>:\<device\>.\<function\>", > + /// e.g. "0000:01:01.0". > + /// > + /// # See also > + /// > + /// [`nvmlDeviceGetSupportedVgpus`]: > <https://docs.nvidia.com/deploy/nvml-api/group__nvmlVgpu.html#group__nvmlVgpu_1ge084b87e80350165859500ebec714274> > + /// [`nvmlDeviceGetHandleByPciBusId_v2`]: > <https://docs.nvidia.com/deploy/nvml-api/group__nvmlDeviceQueries.html#group__nvmlDeviceQueries_1gea7484bb9eac412c28e8a73842254c05> > + /// [`struct nvmlPciInfo_t`]: > <https://docs.nvidia.com/deploy/nvml-api/structnvmlPciInfo__t.html#structnvmlPciInfo__t_1a4d54ad9b596d7cab96ecc34613adbe4> > + #[export] > + fn supported_vgpu_types_for_dev(bus_id: &str) -> Result<Vec<Value>> { > + let nvml = Nvml::init()?; > + let device = nvml.device_by_pci_bus_id(bus_id)?; > + > + build_vgpu_type_list(device.vgpu_supported_types()?) > + }
