Week #6 — The Method to Test
Sachin C -
Hello! Now that my AI model is close to completion, I have to turn an eye to how I plan on measuring the energy consumption of each microcontroller. I don’t want to use a bulky operating system on the microcontroller itself to ensure its internal energy consumption remains relatively low.
To get accurate data, I will be using a combination of hardware and software tools to measure the power draw of each microcontroller under different workloads.
- Using a Voltage and Current Meter
- A power analyzer will be connected to each microcontroller to measure its voltage (V) and current (A) while running my AI model.
- Power consumption is calculated using the formula:
Power (W) = Voltage (V) × Current (A)
- Power Draw Over Time
- By connecting my meter to a computer, I can track power usage in real-time and see how it fluctuates under different loads.
- This will help identify which parts of the AI model require the most energy.
- Idle vs. Active States
- I will measure power usage when the microcontroller is idle versus when it is actively running AI computations.
- This will show how much additional power AI inference requires.
- Power Estimation
- Some microcontrollers have built-in tools for power monitoring.
- ESP32 Power Management API can estimate energy usage in different power modes.
- Raspberry Pi power monitoring tools allow real-time tracking of CPU and GPU energy consumption.
- Some microcontrollers have built-in tools for power monitoring.
I am super excited to get right into it, so this next week will likely be focused on getting together my hardware and beginning to setup each controller with the model.
Thank you for reading, and I’ll see you next week!
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