cisco.intersight.intersight_bios_ai_tuning module – AI-optimized BIOS policy presets for Cisco Intersight

Note

This module is part of the cisco.intersight collection (version 2.18.0).

You might already have this collection installed if you are using the ansible package. It is not included in ansible-core. To check whether it is installed, run ansible-galaxy collection list.

To install it, use: ansible-galaxy collection install cisco.intersight.

To use it in a playbook, specify: cisco.intersight.intersight_bios_ai_tuning.

Synopsis

  • Creates BIOS policies with pre-validated settings optimized for AI and GPU workloads.

  • Provides named tuning profiles that set multiple BIOS knobs at once for common AI use cases.

  • Profiles target NVIDIA H100/B200 GPU servers and Intel/AMD CPU platforms used in Cisco AI Factory.

  • Individual BIOS knobs can be overridden after the preset is applied.

  • For full BIOS knob control, use cisco.intersight.intersight_bios_policy instead.

  • For more information see Cisco Intersight.

Parameters

Parameter

Comments

api_key_id

string / required

Public API Key ID associated with the private key.

If not set, the value of the INTERSIGHT_API_KEY_ID environment variable is used.

api_private_key

path / required

Filename (absolute path) or string of PEM formatted private key data to be used for Intersight API authentication.

If a string is used, Ansible vault should be used to encrypt string data.

Ex. ansible-vault encrypt_string --vault-id tme@/Users/dsoper/Documents/vault_password_file ‘-----BEGIN EC PRIVATE KEY-----

<your private key data>

-----END EC PRIVATE KEY-----’

If not set, the value of the INTERSIGHT_API_PRIVATE_KEY environment variable is used.

api_uri

string

URI used to access the Intersight API.

If not set, the value of the INTERSIGHT_API_URI environment variable is used.

Default: "https://intersight.com/api/v1"

cpu_energy_performance

string

Override the CPU energy performance bias setting.

Choices:

  • "platform-default"

  • "balanced-energy"

  • "balanced-performance"

  • "energy-efficient"

  • "performance"

cpu_performance

string

Override the CPU performance setting from the tuning profile.

Choices:

  • "platform-default"

  • "custom"

  • "enterprise"

  • "high-throughput"

  • "hpc"

cpu_power_management

string

Override the CPU power management setting from the tuning profile.

Choices:

  • "platform-default"

  • "performance"

  • "energy-efficient"

  • "custom"

description

aliases: descr

string

The user-defined description of the BIOS policy.

gpu_count

integer

Number of GPUs to enable via ACS Control (1-8).

Only applicable for gpu_inference and gpu_training profiles.

GPUs beyond this count will have ACS control set to platform-default.

Default: 8

intel_turbo_boost_tech

string

Override the Intel Turbo Boost Technology setting.

Choices:

  • "platform-default"

  • "enabled"

  • "disabled"

name

string / required

The name assigned to the BIOS policy.

The name must be between 1 and 62 alphanumeric characters, allowing special characters :-_.

numa_optimized

string

Override the NUMA optimization setting from the tuning profile.

Choices:

  • "platform-default"

  • "enabled"

  • "disabled"

organization

string

The name of the Organization this resource is assigned to.

Profiles and Policies that are created within a Custom Organization are applicable only to devices in the same Organization.

Default: "default"

sriov

string

Override the SR-IOV setting from the tuning profile.

SR-IOV is required for GPU passthrough in virtualized environments.

Choices:

  • "platform-default"

  • "enabled"

  • "disabled"

state

string

If present, will verify the resource is present and will create if needed.

If absent, will verify the resource is absent and will delete if needed.

Choices:

  • "present" ← (default)

  • "absent"

tags

list / elements=dictionary

List of tags in Key:<user-defined key> Value:<user-defined value> format.

tuning_profile

string / required

The AI tuning profile preset to apply.

gpu_inference optimizes for maximum GPU throughput with low-latency memory access. Sets GPU ACS control enabled, NUMA optimized, hardware P-states disabled for consistent performance, SR-IOV enabled, and memory interleave optimized.

gpu_training optimizes for large-scale GPU training workloads with maximum memory bandwidth. Includes all gpu_inference settings plus maximum power performance tuning, workload configuration set to balanced, and package C-state limit for sustained throughput.

cpu_inference optimizes for CPU-based inference with low-latency tuning. Enables hardware P-states for native performance, Intel Turbo Boost, LLC prefetch, and NUMA optimization without GPU-specific settings.

edge_ai optimizes for Cisco Unified Edge nodes with power-aware AI tuning. Balances performance with power efficiency using energy-efficient turbo, hardware P-states, and NUMA optimization suitable for edge deployment constraints.

Choices:

  • "gpu_inference"

  • "gpu_training"

  • "cpu_inference"

  • "edge_ai"

use_proxy

boolean

If no, it will not use a proxy, even if one is defined in an environment variable on the target hosts.

Choices:

  • false

  • true ← (default)

validate_certs

boolean

Boolean control for verifying the api_uri TLS certificate

Choices:

  • false

  • true ← (default)

Examples

- name: Create GPU inference optimized BIOS policy for 8-GPU server
  cisco.intersight.intersight_bios_ai_tuning:
    api_private_key: "{{ api_private_key }}"
    api_key_id: "{{ api_key_id }}"
    organization: AI-Factory
    name: bios-gpu-inference-h100
    description: BIOS tuning for H100 GPU inference servers
    tuning_profile: gpu_inference
    gpu_count: 8

- name: Create GPU training BIOS policy with power override
  cisco.intersight.intersight_bios_ai_tuning:
    api_private_key: "{{ api_private_key }}"
    api_key_id: "{{ api_key_id }}"
    name: bios-gpu-training
    tuning_profile: gpu_training
    cpu_power_management: performance

- name: Create CPU inference BIOS policy for non-GPU workloads
  cisco.intersight.intersight_bios_ai_tuning:
    api_private_key: "{{ api_private_key }}"
    api_key_id: "{{ api_key_id }}"
    name: bios-cpu-inference
    tuning_profile: cpu_inference
    intel_turbo_boost_tech: enabled

- name: Create edge AI BIOS policy for Unified Edge nodes
  cisco.intersight.intersight_bios_ai_tuning:
    api_private_key: "{{ api_private_key }}"
    api_key_id: "{{ api_key_id }}"
    name: bios-edge-ai
    tuning_profile: edge_ai
    gpu_count: 2

- name: Delete AI BIOS policy
  cisco.intersight.intersight_bios_ai_tuning:
    api_private_key: "{{ api_private_key }}"
    api_key_id: "{{ api_key_id }}"
    name: bios-gpu-inference-h100
    tuning_profile: gpu_inference
    state: absent

Return Values

Common return values are documented here, the following are the fields unique to this module:

Key

Description

api_response

dictionary

The API response output returned by the specified resource.

Returned: always

Sample: {"api_response": {"AcsControlGpu1state": "enabled", "Name": "bios-gpu-inference-h100", "NumaOptimized": "enabled", "ObjectType": "bios.Policy"}}

applied_settings

dictionary

The BIOS settings applied by the tuning profile and any overrides.

Returned: when state is present

Authors

  • Steve Fulmer (@stevefulme1)