allwinner_a64/android/system/extras/simpleperf/demo

Examples of using simpleperf to profile Android applications

Table of Contents

• Introduction
• Profiling Java application
• Profiling Java/C++ application
• Profiling Kotlin application

Introduction

Simpleperf is a native profiler used on Android platform. It can be used to profile Android applications. It's document is at here. Instructions of preparing your Android application for profiling are here. This directory is to show examples of using simpleperf to profile Android applications. The meaning of each directory is as below:

../scripts/                  -- contain simpleperf binaries and scripts.
SimpleperfExamplePureJava/   -- contains an Android Studio project using only Java code.
SimpleperfExampleWithNative/ -- contains an Android Studio project using both Java and C++ code.
SimpleperfExampleOfKotlin/   -- contains an Android Studio project using Kotlin code.

It can be downloaded as below:

$ git clone https://android.googlesource.com/platform/system/extras
$ cd extras/simpleperf/demo

Profiling Java application

Android Studio project: SimpleExamplePureJava
test device: Android O (Google Pixel XL)
test device: Android N (Google Nexus 5X)

steps:

1. Build and install app:

# Open SimpleperfExamplesPureJava project with Android Studio,
# and build this project sucessfully, otherwise the `./gradlew` command below will fail.
$ cd SimpleperfExamplePureJava

# On windows, use "gradlew" instead.
$ ./gradlew clean assemble
$ adb install -r app/build/outputs/apk/app-profiling.apk

2. Record profiling data:

$ cd ../../scripts/
$ python app_profiler.py -p com.example.simpleperf.simpleperfexamplepurejava

3. Show profiling data:

a. show call graph in txt mode
    # On windows, use "bin\windows\x86\simpleperf" instead.
    $ bin/linux/x86_64/simpleperf report -g | more
        If on other hosts, use corresponding simpleperf binary.
b. show call graph in gui mode
    $ python report.py -g
c. show samples in source code
    $ python annotate.py -s ../demo/SimpleperfExamplePureJava
    $ gvim annotated_files/java/com/example/simpleperf/simpleperfexamplepurejava/MainActivity.java
        check the annoated source file MainActivity.java.

Profiling Java/C++ application

Android Studio project: SimpleExampleWithNative
test device: Android O (Google Pixel XL)
test device: Android N (Google Nexus 5X)

steps:

1. Build and install app:

# Open SimpleperfExamplesWithNative project with Android Studio,
# and build this project sucessfully, otherwise the `./gradlew` command below will fail.
$ cd SimpleperfExampleWithNative

# On windows, use "gradlew" instead.
$ ./gradlew clean assemble
$ adb install -r app/build/outputs/apk/app-profiling.apk

2. Record profiling data:

$ cd ../../scripts/
$ python app_profiler.py -p com.example.simpleperf.simpleperfexamplewithnative
    It runs the application and collects profiling data in perf.data, binaries on device in binary_cache/.

3. Show profiling data:

a. show call graph in txt mode
    # On windows, use "bin\windows\x86\simpleperf" instead.
    $ bin/linux/x86_64/simpleperf report -g | more
        If on other hosts, use corresponding simpleperf binary.
b. show call graph in gui mode
    $ python report.py -g
c. show samples in source code
    $ python annotate.py -s ../demo/SimpleperfExampleWithNative
    $ find . -name "native-lib.cpp" | xargs gvim
        check the annoated source file native-lib.cpp.

Profiling Kotlin application

Android Studio project: SimpleExampleOfKotlin
test device: Android O (Google Pixel XL)
test device: Android N (Google Nexus 5X)

steps:

1. Build and install app:

# Open SimpleperfExamplesOfKotlin project with Android Studio,
# and build this project sucessfully, otherwise the `./gradlew` command below will fail.
$ cd SimpleperfExampleOfKotlin

# On windows, use "gradlew" instead.
$ ./gradlew clean assemble
$ adb install -r app/build/outputs/apk/profiling/app-profiling.apk

2. Record profiling data:

$ cd ../../scripts/
$ python app_profiler.py -p com.example.simpleperf.simpleperfexampleofkotlin
    It runs the application and collects profiling data in perf.data, binaries on device in binary_cache/.

3. Show profiling data:

a. show call graph in txt mode
    # On windows, use "bin\windows\x86\simpleperf" instead.
    $ bin/linux/x86_64/simpleperf report -g | more
        If on other hosts, use corresponding simpleperf binary.
b. show call graph in gui mode
    $ python report.py -g
c. show samples in source code
    $ python annotate.py -s ../demo/SimpleperfExampleOfKotlin
    $ find . -name "MainActivity.kt" | xargs gvim
        check the annoated source file MainActivity.kt.