# tuned-amdgpu hacky solution to integrate AMDGPU power profile control in `tuned` with Ansible ## Notable variables - ``: Accepts a float from (presumably) 0.0 to 1.0. Allows max GPU power consumption to be controlled. Default: `0.9` for 90%, roughly stock 3D peak. - `card`: Sets the `card#` to use in the qualified sysfs path `/sys/class/drm/{{ card }}/device/pp_power_profile_mode`. Default: `card0` - `base_profiles`: List of base tuned profiles to clone in the new AMDGPU profiles. Defaults: - `desktop` - `network-latency` - `powersave` - `amdgpu_profiles`: Mapping of AMDGPU power profiles (`name`/`value`) defined in the `sysfs` path above. Varies, sample is with a 6900XT. Defaults: - `{ name: 'bootup_default', value: 0 }` - `{ name: '3D_fullscreen', value: 1 }` - `{ name: 'powersaving', value: 2 }` - `{ name: 'video', value: 3 }` - `{ name: 'VR', value: 4 }` - `{ name: 'compute', value: 5 }` - `{ name: 'custom', value: 6 }` ## Example profiles/output ``` $ tuned-adm profile Available profiles: - accelerator-performance - Throughput performance based tuning with disabled higher latency STOP states - balanced - General non-specialized tuned profile - desktop - Optimize for the desktop use-case - desktop_amdgpu_3D_fullscreen- desktop based profile with AMDGPU pp_power_profile_mode = 1 (3D_fullscreen) - desktop_amdgpu_VR - desktop based profile with AMDGPU pp_power_profile_mode = 4 (VR) - desktop_amdgpu_bootup_default- desktop based profile with AMDGPU pp_power_profile_mode = 0 (bootup_default) - desktop_amdgpu_compute - desktop based profile with AMDGPU pp_power_profile_mode = 5 (compute) - desktop_amdgpu_custom - desktop based profile with AMDGPU pp_power_profile_mode = 6 (custom) - desktop_amdgpu_powersaving - desktop based profile with AMDGPU pp_power_profile_mode = 2 (powersaving) - desktop_amdgpu_video - desktop based profile with AMDGPU pp_power_profile_mode = 3 (video) - hpc-compute - Optimize for HPC compute workloads - intel-sst - Configure for Intel Speed Select Base Frequency - latency-performance - Optimize for deterministic performance at the cost of increased power consumption - network-latency - Optimize for deterministic performance at the cost of increased power consumption, focused on low latency network performance - network-latency_amdgpu_3D_fullscreen- network-latency based profile with AMDGPU pp_power_profile_mode = 1 (3D_fullscreen) - network-latency_amdgpu_VR - network-latency based profile with AMDGPU pp_power_profile_mode = 4 (VR) - network-latency_amdgpu_bootup_default- network-latency based profile with AMDGPU pp_power_profile_mode = 0 (bootup_default) - network-latency_amdgpu_compute- network-latency based profile with AMDGPU pp_power_profile_mode = 5 (compute) - network-latency_amdgpu_custom- network-latency based profile with AMDGPU pp_power_profile_mode = 6 (custom) - network-latency_amdgpu_powersaving- network-latency based profile with AMDGPU pp_power_profile_mode = 2 (powersaving) - network-latency_amdgpu_video- network-latency based profile with AMDGPU pp_power_profile_mode = 3 (video) - network-throughput - Optimize for streaming network throughput, generally only necessary on older CPUs or 40G+ networks - optimize-serial-console - Optimize for serial console use. - powersave - Optimize for low power consumption - powersave_amdgpu_3D_fullscreen- powersave based profile with AMDGPU pp_power_profile_mode = 1 (3D_fullscreen) - powersave_amdgpu_VR - powersave based profile with AMDGPU pp_power_profile_mode = 4 (VR) - powersave_amdgpu_bootup_default- powersave based profile with AMDGPU pp_power_profile_mode = 0 (bootup_default) - powersave_amdgpu_compute - powersave based profile with AMDGPU pp_power_profile_mode = 5 (compute) - powersave_amdgpu_custom - powersave based profile with AMDGPU pp_power_profile_mode = 6 (custom) - powersave_amdgpu_powersaving- powersave based profile with AMDGPU pp_power_profile_mode = 2 (powersaving) - powersave_amdgpu_video - powersave based profile with AMDGPU pp_power_profile_mode = 3 (video) - throughput-performance - Broadly applicable tuning that provides excellent performance across a variety of common server workloads - virtual-guest - Optimize for running inside a virtual guest - virtual-host - Optimize for running KVM guests ```