@@ -24,3 +24,4 @@
Lens driver requirements <lens_driver_requirements>
Python Bindings <python-bindings>
Camera Sensor Model <camera-sensor-model>
+ SoftwareISP Benchmarking <software-isp-benchmarking>
@@ -80,6 +80,7 @@ if sphinx.found()
'lens_driver_requirements.rst',
'python-bindings.rst',
'sensor_driver_requirements.rst',
+ 'software-isp-benchmarking.rst',
'../README.rst',
]
new file mode 100644
@@ -0,0 +1,77 @@
+.. SPDX-License-Identifier: CC-BY-SA-4.0
+
+.. _software-isp-benchmarking:
+
+Software ISP benchmarking
+=========================
+
+The Software ISP is particularly sensitive to performance regressions therefore
+it is a good idea to always benchmark the Software ISP before and after making
+changes to it and ensure that there are no performance regressions.
+
+DebayerCpu class builtin benchmark
+----------------------------------
+
+The DebayerCpu class has a builtin benchmark. This benchmark measures the time
+spent on processing (collecting statistics and debayering) only, it does not
+measure the time spent on capturing or outputting the frames.
+
+The builtin benchmark always runs. So this can be used by simply running "cam"
+or "qcam" with a pipeline using the Software ISP.
+
+When it runs it will skip measuring the first 30 frames to allow the caches and
+the CPU temperature (turbo-ing) to warm-up and then it measures 30 fps and shows
+the total and per frame processing time using an info level log message:
+
+.. code-block:: text
+
+ INFO Debayer debayer_cpu.cpp:907 Processed 30 frames in 244317us, 8143 us/frame
+
+To get stable measurements it is advised to disable any other processes which
+may cause significant CPU usage (e.g. disable wifi, bluetooth and browsers).
+When possible it is also advisable to disable CPU turbo-ing and
+frequency-scaling.
+
+For example when benchmarking on a Lenovo ThinkPad X1 Yoga Gen 8, with the
+charger plugged in, the CPU can be fixed to run at 2 GHz using:
+
+.. code-block:: shell
+
+ sudo x86_energy_perf_policy --turbo-enable 0
+ sudo cpupower frequency-set -d 2GHz -u 2GHz
+
+with these settings the builtin bench reports a processing time of ~7.8ms/frame
+on this laptop for FHD SGRBG10 (unpacked) bayer data.
+
+Measuring power consumption
+---------------------------
+
+Since the Software ISP is often used on mobile devices it is also important to
+measure power consumption and ensure that that does not regress.
+
+For example to measure power consumption on a Lenovo ThinkPad X1 Yoga Gen 8 it
+needs to be running on battery and it should be configured with its
+platform-profile (/sys/firmware/acpi/platform_profile) set to balanced and with
+its default turbo and frequency-scaling behavior to match real world usage.
+
+Then start qcam to capture a FHD picture at 30 fps and position the qcam window
+so that it is fully visible. After this run the following command to monitor the
+power consumption:
+
+.. code-block:: shell
+
+ watch -n 10 cat /sys/class/power_supply/BAT0/power_now /sys/class/hwmon/hwmon6/fan?_input
+
+Note this not only measures the power consumption in µW it also monitors the
+speed of this laptop's 2 fans. This is important because depending on the
+ambient temperature the 2 fans may spin up while testing and this will cause an
+additional power consumption of approx. 0.5 W messing up the measurement.
+
+After starting qcam + the watch command let the laptop sit without using it for
+2 minutes for the readings to stabilize. Then check that the fans have not
+turned on and manually take a couple of consecutive power readings and average
+these.
+
+On the example Lenovo ThinkPad X1 Yoga Gen 8 laptop this results in a measured
+power consumption of approx. 13 W while running qcam versus approx. 4-5 W while
+setting idle with its OLED panel on.