From CPU utilization to carbon emissions

Tags

carbon, teads, power-curve

Observations

This manifest requires the following observations:

• CPU utilization
• thermal design power of the processors
• number of vCPUs allocated to the application under observation
• total number of vCPUs available on the cloud instance being used
• the name of the cloud instance type being used
• the grid carbon intensity for the grid powering the data center

Impacts

This pipeline takes the observations described above, and generates carbon emissions in each timestep, expressed in gCO2e.

Scope

This pipeline takes into account the operational carbon of the server running our application. This includes the energy used to run the application, calculated from CPU and memory utilization. It does not account for any embodied carbon, nor networking energy, nor anything related to the end user. In real applications, the pipeline described here will be part of a much larger manifest that considers other parts of the system.

Description

The Teads CPU power curve CPU utilization (as a percentage) against a scaling factor that can be applied to the CPUs thermal design power to estimate the power drawn by the CPU in Watts.

The research underpinning the curve was summarized in a pair of blog posts:

TEADS Engineering: Buildiong an AWS EC2 Carbon Emissions Dataset

Teads Engineering: Estimating AWS EC2 Instances Power Consumption

The curve has become very widely used as a general purpose utilization-to-wattage converter for CPUs, despite the fact that it does not generalize well.

The wattage can be transformed into energy by doing the following:

1. Measure your CPU utilization
2. Determine the thermal design power of your processor
3. Determine the scaling factor for your CPU utilization by interpolating the Teads curve
4. Determine the power drawn by your CPU by multiplying your scaling factor by the CPU's thermal design power
5. Perform a unit conversion to convert power in Watts to energy in kwH
6. Scale the energy estimated for the entire chip to the portion of the chip that is actually in use.

These steps can be executed in IF using just three plugins:

• Interpolate
• Multiply
• Divide

Common patterns

The logical flow from CPU utilization to carbon via a power-curve and thermal design power is a common pattern that is likely to be re-used elsewhere.

Constants and coefficients:

parameter	description	value	unit	source
x, y	Points on power curve relating CPU utilization to a coefficient used to scale the processor's thermal design power	x: [0, 10, 50, 100], y: [0.12, 0.32, 0.75, 1.02]	dimensionless	Davy, 2021
grid-carbon-intensity	the carbon emitted per unit energy from the electrical grid	750	gCO2e/kWh	approximates global average

Assumptions and limitations

The following are assumed to be true in this manifest:

• the power curve relating CPU utilization to power is appropriate for the processor being used to run our application
• the temporal granularity of the observations are sufficient to accurately capture the behaviour of our application
• the grid carbon intensity is sufficiently accurate for the location where the computational work is done

Components

There is only one component in this example. It represents the entire application. The component pipeline looks as follows:

pipeline:
  compute:
    - interpolate
    - cpu-factor-to-wattage
    - wattage-times-duration
    - wattage-to-energy-kwh
    - calculate-vcpu-ratio
    - correct-cpu-energy-for-vcpu-ratio
    - energy-to-carbon

Plugins

Interpolate

The interpolate plugin is used once. The instance is named interpolate. It is used to interpolate the curve relating CPU utilization and thermal-design-power factor so that the right value can be retrieved for the observed CPU utilization at each timestep.

config

method: linear
x: [0, 10, 50, 100]
y: [0.12, 0.32, 0.75, 1.02]
input-parameter: cpu/utilization
output-parameter: cpu-factor

Multiply

The Multiply plugin is used several times. The instances are:

• cpu-factor-to-wattage: used to multiply the thermal design power of the processor by the factor returned from the power curve interpolation, yielding power in Watts.
• wattage-times-duration: used to multiply the power in Watts by the duration of each timestep, yielding energy in W/duration.
• energy-to-carbon: used to convert energy expended to carbon emitted.

config

cpu-factor-to-wattage:
  input-parameters:
    - cpu-factor
    - cpu/thermal-design-power
  output-parameter:
    - cpu-wattage

wattage-times-duration:
  input-parameters:
    - cpu-wattage
    - duration
  output-parameter:
    - cpu-wattage-times-duration

energy-to-carbon:
  input-parameters:
    - grid-carbon-intensity
    - energy-cpu-kwh
  output-parameter:
    - carbon

Divide

The Divide plugin is used several times in this manifest. The instances are:

• wattage-to-energy-kwh. used to convert energy in W/duration to kWh.
• calculate-vcpu-ratio: used to calculate the ratio of allocated vCPUs to total vCPUS
• correct-cpu-energy-for-vcpu-ratio: used to scale the CPU energy by the vCPU ratio

config

wattage-to-energy-kwh:
  numerator: cpu-wattage-times-duration
  denominator: 3600000
  output: cpu-energy-raw

calculate-vcpu-ratio:
  numerator: vcpus-total
  denominator: vcpus-allocated
  output: vcpu-ratio

correct-cpu-energy-for-vcpu-ratio:
  numerator: cpu-energy-raw
  denominator: vcpu-ratio
  output: cpu/energy

Manifest

name: teads curve demo
description:
tags:
initialize:
  plugins:
    interpolate:
      path: builtin
      method: Interpolation
      config:
        method: linear
        x:
          - 0
          - 10
          - 50
          - 100
        'y':
          - 0.12
          - 0.32
          - 0.75
          - 1.02
        input-parameter: cpu/utilization
        output-parameter: cpu-factor
    cpu-factor-to-wattage:
      path: builtin
      method: Multiply
      config:
        input-parameters:
          - cpu-factor
          - thermal-design-power
        output-parameter: cpu-wattage
    wattage-times-duration:
      path: builtin
      method: Multiply
      config:
        input-parameters:
          - cpu-wattage
          - duration
        output-parameter: cpu-wattage-times-duration
    wattage-to-energy-kwh:
      path: builtin
      method: Divide
      config:
        numerator: cpu-wattage-times-duration
        denominator: 3600000
        output: cpu-energy-raw
    calculate-vcpu-ratio:
      path: builtin
      method: Divide
      config:
        numerator: vcpus-total
        denominator: vcpus-allocated
        output: vcpu-ratio
    correct-cpu-energy-for-vcpu-ratio:
      path: builtin
      method: Divide
      config:
        numerator: cpu-energy-raw
        denominator: vcpu-ratio
        output: cpu-energy-kwh
    energy-to-carbon:
      path: builtin
      method: Multiply
      config:
        input-parameters:
          - grid-carbon-intensity
          - cpu-energy-kwh
        output-parameter: carbon
execution:
  command: >-
    /home/user/.npm/_npx/1bf7c3c15bf47d04/node_modules/.bin/ts-node
    /home/user/if/src/index.ts -m manifests/examples/teads-curve.yml
  environment:
    if-version: 0.6.0
    os: macOS
    os-version: 14.6.1
    node-version: 18.20.4
    date-time: 2024-10-03T15:11:48.498Z (UTC)
    dependencies:
      - '@babel/core@7.22.10'
      - '@babel/preset-typescript@7.23.3'
      - '@commitlint/cli@18.6.0'
      - '@commitlint/config-conventional@18.6.0'
      - '@grnsft/if-core@0.0.25'
      - '@jest/globals@29.7.0'
      - '@types/jest@29.5.8'
      - '@types/js-yaml@4.0.9'
      - '@types/luxon@3.4.2'
      - '@types/node@20.9.0'
      - axios-mock-adapter@1.22.0
      - axios@1.7.2
      - cross-env@7.0.3
      - csv-parse@5.5.6
      - csv-stringify@6.4.6
      - fixpack@4.0.0
      - gts@5.2.0
      - husky@8.0.3
      - jest@29.7.0
      - js-yaml@4.1.0
      - lint-staged@15.2.2
      - luxon@3.4.4
      - release-it@16.3.0
      - rimraf@5.0.5
      - ts-command-line-args@2.5.1
      - ts-jest@29.1.1
      - typescript-cubic-spline@1.0.1
      - typescript@5.2.2
      - winston@3.11.0
      - zod@3.23.8
  status: success
tree:
  children:
    child:
      pipeline:
        observe:
        regroup:
        compute:
          - interpolate
          - cpu-factor-to-wattage
          - wattage-times-duration
          - wattage-to-energy-kwh
          - calculate-vcpu-ratio
          - correct-cpu-energy-for-vcpu-ratio
          - energy-to-carbon
      defaults:
        thermal-design-power: 100
        vcpus-total: 8
        vcpus-allocated: 2
        grid-carbon-intensity: 750
      inputs:
        - timestamp: 2023-08-06T00:00
          duration: 360
          cpu/utilization: 1
          carbon: 30
        - timestamp: 2023-09-06T00:00
          duration: 360
          carbon: 30
          cpu/utilization: 10
        - timestamp: 2023-10-06T00:00
          duration: 360
          carbon: 30
          cpu/utilization: 50
        - timestamp: 2023-10-06T00:00
          duration: 360
          carbon: 30
          cpu/utilization: 100
      outputs:
        - timestamp: 2023-08-06T00:00
          duration: 360
          cpu/utilization: 1
          carbon: 30
          thermal-design-power: 100
          vcpus-total: 8
          vcpus-allocated: 2
          grid-carbon-intensity: 750
          cpu-factor: 0.13999999999999999
          cpu-wattage: 13.999999999999998
          cpu-wattage-times-duration: 5039.999999999999
          cpu-energy-raw: 0.0013999999999999998
          vcpu-ratio: 4
          cpu-energy-kwh: 0.00034999999999999994
        - timestamp: 2023-09-06T00:00
          duration: 360
          carbon: 30
          cpu/utilization: 10
          thermal-design-power: 100
          vcpus-total: 8
          vcpus-allocated: 2
          grid-carbon-intensity: 750
          cpu-factor: 0.32
          cpu-wattage: 32
          cpu-wattage-times-duration: 11520
          cpu-energy-raw: 0.0032
          vcpu-ratio: 4
          cpu-energy-kwh: 0.0008
        - timestamp: 2023-10-06T00:00
          duration: 360
          carbon: 30
          cpu/utilization: 50
          thermal-design-power: 100
          vcpus-total: 8
          vcpus-allocated: 2
          grid-carbon-intensity: 750
          cpu-factor: 0.75
          cpu-wattage: 75
          cpu-wattage-times-duration: 27000
          cpu-energy-raw: 0.0075
          vcpu-ratio: 4
          cpu-energy-kwh: 0.001875
        - timestamp: 2023-10-06T00:00
          duration: 360
          carbon: 30
          cpu/utilization: 100
          thermal-design-power: 100
          vcpus-total: 8
          vcpus-allocated: 2
          grid-carbon-intensity: 750
          cpu-factor: 1.02
          cpu-wattage: 102
          cpu-wattage-times-duration: 36720
          cpu-energy-raw: 0.0102
          vcpu-ratio: 4
          cpu-energy-kwh: 0.00255