Hey there! Let's tackle this thermal testing challenge for your embedded Snapdragon Android device—since you've been stuck on this for days, I’ll break down practical, actionable steps tailored exactly to your setup:

Most Snapdragon-powered Android devices expose thermal sensor data through system files, which you can access via ADB (either through Vysor's built-in terminal or a computer-side ADB connection):

• Check sysfs thermal zones: Run this command in the shell to get raw temperature readings:

  cat /sys/class/thermal/thermal_zone*/temp
  

  Values are in millidegrees Celsius (e.g., 62000 = 62°C). To see which component each zone corresponds to, check the type file in each zone directory:

  cat /sys/class/thermal/thermal_zone*/type
  

  This will tell you if you're reading CPU, GPU, modem, or other component temperatures.
• Snapdragon-specific thermal nodes: Some devices have additional Qualcomm-specific nodes under /sys/devices/virtual/thermal/. If your device is rooted, you might also access thermal-engine debug commands to get more granular data.

Since you need to simulate high-intensity codec work, generic CPU/GPU load tools won’t cut it—focus on workloads that mirror your actual use case:

• FFmpeg for hardware-accelerated codec testing: Cross-compile FFmpeg for your device’s architecture (armv7-a for most Android 5.0 Snapdragons) with support for Qualcomm’s OpenMAX (OMX) codecs. Then run a looped transcode command like this to stress the codec hardware:

  while true; do ffmpeg -i high_res_input.mp4 -c:v h264_omx -b:v 15M -f null -; done
  

  Use a high-resolution (1080p/4K) input file to maximize load.
• MediaCodec-based Android app: If you’re comfortable with Android development, build a simple APK that uses the MediaCodec API to repeatedly encode/decode a video stream. This directly uses the device’s native codec framework, just like your intended workload will.
• GPU complement (if codec relies on GPU): Since your device supports OpenGL ES 3.0, use a tool like glmark2 (cross-compiled for your device) to run GPU-intensive shader tests alongside the codec workload—this mimics real-world combined load.

You need to track how temperatures change as load runs—automate this to avoid manual checks:

• Shell script for logging: Create a simple script to record temperatures, codec process CPU usage, and timestamps to a log file:

  #!/bin/sh
  touch thermal_test_log.txt
  while true; do
      echo "=== $(date) ===" >> thermal_test_log.txt
      # Log thermal zone temps and their types
      for zone in /sys/class/thermal/thermal_zone*; do
          echo "$(basename $zone) ($(cat $zone/type)): $(cat $zone/temp) m°C" >> thermal_test_log.txt
      done
      # Log codec process resource usage
      top -n 1 | grep -E "(ffmpeg|mediacodec)" >> thermal_test_log.txt
      sleep 5
  done
  

  Push this script to your device via ADB, make it executable with chmod +x script.sh, and run it in the background.
• Post-test visualization: Pull the log file to your computer with adb pull thermal_test_log.txt and use tools like Excel or Python’s Matplotlib to plot temperature trends over time—this makes it easy to spot thermal throttling or peak temperatures.

• Physical temperature validation: System-reported temps might have slight offsets. Use an infrared thermometer to measure the Snapdragon SoC’s surface directly, then cross-reference with sysfs data to calibrate your readings.
• Control environmental conditions: Test in a stable, cool environment to eliminate external heat interference—this ensures your data reflects only the device’s thermal output under load.
• Root considerations: If some thermal nodes or tools are restricted, check if your device has manufacturer-provided debug access (common for embedded systems) before going through the hassle of unlocking/rooting.

内容的提问来源于stack exchange，提问作者user1689158