profcollect: Docs for processing traces

Test: N/A
Change-Id: I9c932e0d87b5f378d16ae100fa37365fe1b625ed

1 files changed, 70 insertions, 1 deletions

diff --git a/profcollectd/README.md b/profcollectd/README.md
index a0ce4024..dba75a2c 100644
--- a/profcollectd/README.md
+++ b/profcollectd/README.md
@@ -5,7 +5,7 @@ platform applications.
 
 Profcollect can only be enabled on `userdebug` or `eng` builds.
 
-## Supported platforms
+## Supported Platforms
 
 Currently Profcollect only supports collecting profiles from Coresight ETM enabled ARM devices.
 
@@ -32,10 +32,79 @@ are controlled by the following configurations:
 
 | Event      | Config                 |
 |------------|------------------------|
+| Periodic   | collection\_interval   |
 | App launch | applaunch\_trace\_freq |
 
 Setting the frequency value to `0` disables collection for the corresponding event.
 
+### Processing
+
+The raw tracing data needs to be combined with the original binary to create the AutoFDO branch
+list. This is a costly process, thus it is done separately from the profile collection. Profcollect
+attempts to process all the traces when the device is idle and connected to a power supply. It can
+also be initiated by running:
+
+```
+adb shell profcollectctl process
+```
+
 ### Reporting
 
+#### Manual
+
+After actively using the device for a period of time, the device should have gathered enough data to
+generate a good quality PGO profile that represents typical system usage. Run the following command
+to create a profile report:
+
+```
+$ adb shell profcollectctl report
+Creating profile report
+Report created at: 12345678-0000-abcd-8000-12345678abcd
+```
+
+You can then fetch the report by running (under root):
+
+```
+adb pull /data/misc/profcollectd/report/12345678-0000-abcd-8000-12345678abcd.zip
+```
+
+#### Automated Uploading to Server
+
 *In development*
+
+### Post Processing
+
+For each trace file, run:
+
+```
+simpleperf inject \
+    -i {TRACE_FILE_NAME} \
+    -o {OUTPUT_FILE_NAME}.data \
+    --binary {BINARY_NAME} \
+    --symdir out/target/product/{PRODUCT_NAME}/symbols
+```
+
+Afterwards, run [AutoFDO](https://github.com/google/autofdo) to generate Clang PGO profiles:
+
+```
+create_llvm_prof \
+    --profiler text \
+    --binary=${BINARY_PATH} \
+    --profile=${INPUT_FILE_NAME} \
+    --out={OUTPUT_FILE_NAME}.profdata
+```
+
+Finally, merge all the PGO profiles into one profile:
+
+```
+find {INPUT_DIR} -name *.profdata > proflist
+prebuilts/clang/host/linux-x86/llvm-binutils-stable/llvm-profdata merge \
+    --binary \
+    --sample \
+    --input-files proflist \
+    --output merged.profdata
+```
+
+More profile data usually generates better quality profiles. You may combine data from multiple
+devices running the same build to improve profile quality, and/or reduce the performance impact for
+each device (by reducing collection frequency).