Android GPU Inspector Developer Documentation

See vulkan_generator/DEVDOC.md vulkan_generator specific build instructions.

Build instructions

Setup to run presubmit tests locally

Before creating a pull-request, check that your code can compile and that the presubmit tests pass.

To be able to run the presubmit tests locally, install the following:

# Buildifier
go get github.com/bazelbuild/buildtools/buildifier

# Buildozer
go get github.com/bazelbuild/buildtools/buildozer

# Clang format 11

## On Debian-based Linux (see https://releases.llvm.org/download.html for binaries)

apt-get install clang-format-11

## On macOS
brew install clang-format@11

## Make sure to set the CLANG_FORMAT environment variable, e.g. in bash:

export CLANG_FORMAT=clang-format-11

# Python

## On macOS version 12.6.1 and later intall the XCode command line tools and symlink python to python3

sudo ln -s /Library/Developer/CommandLineTools/usr/bin/python3 /Library/Developer/CommandLineTools/usr/bin/python

# autopep8

python3 -m pip install autopep8

With the above setup, you can run presubmit tests locally with:

./kokoro/presubmit/presubmit.sh

Setup Go development

This project contains Go code, but it does not have the file hierarchy of regular Go projects (this is due to the use of Bazel as a build system). The cmd/gofuse utility enables to re-create the file hierarchy expected by Go tools. Note, however, cmd/gofuse is not supported on Windows, but it is not required to build/develop AGI either. The steps described here are optional and are only intended to facilitate working on the AGI codebase using an IDE or other Go tooling.

# Make sure to build to have all compile-time generated files
cd <path-to-agi-source>
bazel build pkg

# Prepare a agi-gofuse directory **outside of the AGI checkout directory**
mkdir <path-outside-agi-source>/agi-gofuse

# Run gofuse with the previous directory as a target
bazel run //cmd/gofuse -- -dir <path-to-agi-gofuse>

# If the previous command fails to correctly guess the sub-directory under `bazel-out`,
# please pass it with the command below. For example if you build on Windows, the
# standard <bazelout-subdir> is `x64_windows-fastbuild`. If you build on Linux with
# `bazel build -c dbg pkg`, the <bazelout-subdir> is `k8-dbg`.
bazel run //cmd/gofuse -- -dir <path-to-agi-gofuse> -bazelout <bazelout-subdir>

# Build the package again to output the original compile-time generated files again.
bazel build pkg

# Add agi-gofuse directory to your GOPATH environment variable.
# On Linux, with a bash shell, you can add the following to your ~/.bashrc file:
export GOPATH="${GOPATH:+${GOPATH}:}<path-to-agi-gofuse>"
# On other configurations, please search online how to add/edit environment variables.

After adding the gofuse directory to your GOPATH, Go tools should work as expected. You can edit files under the newly populated gofuse directory. You should still compile under the original AGI checkout directory.

Despite its name, the gofuse command does NOT use FUSE (filesystem in userspace). It just creates directories and links to source files, including generated files. It is a good idea to re-run gofuse from time to time, to re-sync links to potential new files.

In terms of editor, VsCode has good Go support thanks to its Go extension. With the GOPATH setup to gofuse and opening the <path-to-agi-gofuse> directory, as the root of your workspace, you should get some jump-to-definition and autocomplete features working. Make sure to edit the files through their link found under the gofuse directory.

How to Debug

You can start a debug build of gapis / gapic or a client under this debugger. To build in debug mode, use the -c dbg Bazel flag, e.g.:

bazel build -c dbg pkg

The recommended Go debugger is delve.

Debugging Gapic

Gapic, the AGI UI, is written in Java. Gapic is launched with java by gapid Go code in //cmd/agi/main.go.

Debugging gapic java code can be done by setting the AGI_GAPIC_DEBUG_PORT=<port_no> environment variable in the shell in which you launch AGI. When AGI_GAPIC_DEBUG_PORT is set, AGI will suspend and wait for the debugger to attach.

Using vscode as an example, configure for attach using a simple debugger launch configuration:

Choose the Run & Debug pane in vscode.
In the top left corner, from the RUN AND DEBUG menu, choose Add Configuration....
With AGI_GAPIC_DEBUG_PORT set to 8000, add this launch configuration:

{
    "type": "java",
    "name": "Java Attach",
    "request": "attach",
    "hostName": "localhost",
    "port": "8000"
}

With vscode configured, launch AGI using bazel in your shell as usual: bazel run -c dbg pkg. You should see the following output: Waiting for java debugger to attach to port: 8000. Now debug from vscode normally using the new launch configuration that you you added in step (3) above.

Debugging Gapis

To debug gapis, you can do:

dlv exec ./bazel-bin/pkg/gapis -- -enable-local-files -persist -rpc localhost:8888

You can then use dlv commands to add breakpoints, and actually start GAPIS, e.g.:

(dlv) break gapis/server/server.go:228

(dlv) continue  # this actually starts gapis

See delve documentation on how to specify a breakpoint location, there are more convenient alternatives than path/to/file:line

Once gapis is started, you can run a client to interact with it and hit somes breakpoints:

# in another terminal
./bazel-bin/pkg/gapit <verb> -gapis-port 8888 <verb args>

Debugging a client

If you want to debug a client like gapit, just start it under dlv:

dlv exec ./bazel-bin/pkg/gapit <verb> <verb args>

Debugging a test

You can build a test in debug mode and then start it under dlv.

For instance:

bazel test --cache_test_results=no -c dbg //core/data/slice:go_default_test

In practice, on Linux this builds and runs a test executable that is located at ./bazel-out/k8-dbg/bin/core/data/slice/linux_amd64_debug/go_default_test, you will have to adapt the k8-dbg part will be different on other platforms. To debug a specific test, you can start this executable under dlv:

$ dlv exec ./bazel-out/k8-dbg/bin/core/data/slice/linux_amd64_debug/go_default_test -- -test.run TestReplace
Type 'help' for list of commands.
(dlv) break TestReplace
Breakpoint 1 set at 0x5f5d4b for github.com/google/gapid/core/data/slice_test.TestReplace() core/data/slice/slice_test.go:26

Use a Delve init script

To automate a delve startup sequence, you can edit a script of delve commands to be executed when delve starts. The script looks like:

# This is a comment.
break gapis/server/server.go:228

# add a second breakpoint, with a condition for it to trigger
break gapis/foo/bar.go:123
condition 2 some_variable == 42

# launch program
continue

And you can pass this script to delve using the --init flag:

dlv exec --init my-delve-init-script.txt <program to debug...>

Integration with an IDE

If you want to interact with the debugger via your editor or IDE, be aware that delve will think file paths start from the AGI top directory, and not your root directory. This is very likely due to Bazel compilation. You may have to find workarounds if you call delve from an editor/IDE which consider the file paths to start from another directory, typically your root directory. There may be a way to adjust using GOPATH to tell to your IDE a possible root for filename lookups.

See the workaround for VSCode below, any help to fix it for other IDEs is very welcome!

Integration with VSCode and Delve

Follow these steps to use the delve debugger for Go with VSCode to debug gapis.

Make sure to complete the Go setup above for AGI.
Settings file: There are two settings file(settings.json) that can be written.
- Global one that applies to all projects that can be opened with Ctrl + Shift + P and Preferences: Open Settings (JSON). Add this line to ensure that you have a stable tools directory: "go.toolsGopath": "<path-to-go-plugin-tools-folder>",
- Local one is under .vscode folder in your project folder. Create one if it does not already exist and add this line to your local settings to be able to search source code in AGI: "go.gopath": "<path-to-agi-gofuse>",
Launch file: Create a launch.json file under the workspace directory with Ctrl + Shift + P and Debug: Open launch.json
Paste the following as one of the launch configurations. This will ensure that there is a launch configuration for attaching to Delve.

{
    ...
    "configurations": [
        ...,
        {
            "name": "Attach to Delve",
            "type": "go",
            "request": "attach",
            "mode": "remote",
            "apiVersion": 2,
            "remotePath": "",
            "cwd": "`<path-to-agi-gofuse>`",
            "dlvLoadConfig": {
                "followPointers": true,
                "maxVariableRecurse": 1,
                "maxStringLen": 120,
                "maxArrayValues": 120,
                "maxStructFields": -1
            },
            "host": <host>,
            "port": <port>,
        },
    ],
    ...
}

As an example, <host> could be 127.0.0.1 and <port> could be 1234.

Start delve in headless mode in the AGI root folder.

dlv exec --headless --listen=<host>:<port> --api-version 2 ./bazel-bin/pkg/gapis -- <gapis-arguments>

The command below will allow using port 1234 (or any other preferred port) to connect to delve from VSCode.

dlv exec --headless --listen=127.0.0.1:1234 --api-version 2 ./bazel-bin/pkg/gapis -- -persist -rpc localhost:8888

Start debugging with Debug->Start Debugging (on Linux with F5) and make sure Attach to Delve is selected as the launch configuration.
Now VSCode can interact with Delve and can be used for debugging gapis in VSCode UI instead of the command line. Enjoy your debugging :)

This allows you to put breakpoint at any line in AGI Go source code regardless if they are handwritten, generated or in Go Standard Library. For the generated file, you can put the breakpoints under the bazel-bin/ or bazel-out/ folder and the debugger will still find it under the fuse directory during debugging and open it. The only downside is you will have two versions of the same file but this is the only working workaround until Go Plugin supports bazel-generated files.

How to debug via printing message

You can use the built-in logging functions to place debug prints.

In Go:

import (
	// ...
	"github.com/google/gapid/core/log"
)

// ...
	log.E(ctx, "Here debug print, myVar: %v", myVar)

In C++:

#include "core/cc/log.h"

// ...
    GAPID_ERROR("Here debug print, myStr: %s", myStr)

The usual logging levels are available, listed for instance with gapit -fullhelp:

$ ./bazel-bin/pkg/gapit -fullhelp
...
-log-level value
	The severity to enable logs at [one of: "Verbose", "Debug", "Info", "Warning", "Error", "Fatal"] (default Info)

The Error level is recommended when adding debug print, to make sure it is not filtered away.

How to debug a replay crash

The replayer uses breakpad to catch and optionnaly report crashes.

If you want to analyze a replay crash with a debugger, on 64 bits Android (for other platforms, adapt as necessary):

Start the replayer with the --wait-for-debugger flag, e.g. ./gapit screenshot --gapir-args '--wait-for-debugger' mytrace.gfxtrace.
Wait for the replayer to launch on the device.
Attach your debugger to the replayer app (com.google.android.gapid.arm64v8a/com.google.android.gapid.ReplayerActivity).
Once attached, you probably want to add a breakpoint at CrashHandler::handleMinidump in order to break upon a crash, before it is reported to the server.
When you attach, the replayer is spin-waiting in the loop defined in core/cc/android/debugger.cpp. To break this loop, use the debugger to set gIsDebuggerAttached = true before continuing execution.

Note that while you attach the debugger and setup the breakpoint, the server might timeout waiting for a gRPC connection. You may increase this timeout by editing the gapir/client:gRPCConnectTimeout constant.

GAPIS build-time options to help with debugging

See gapis/config/config.go for a list of various build-time config options that can help with debugging.

How to profile AGI internals

GAPIS

The server has instrumentation to output profiling information:

$ ./agi/gapis --fullhelp
[...]
  -profile-pprof
	enable pprof profiling
  -profile-trace string
	write a trace to file
[...]

The -profile-trace option generates a trace that can be open in Chrome via chrome://tracing, or using Perfetto web UI.

The gapit and agi (UI starter) clients can pass these arguments to gapis via -gapis-args, e.g.:

# GAPIT
./agi/gapit <verb> -gapis-args '-profile-trace my-profile-trace.out' <verb arguments>

# GAPIC
./agi/agi -gapis-args '-profile-trace my-profile-trace.out' foobar.gfxtrace

On-device: GAPII, GAPIR

To profile the interceptor GAPII and the replayer GAPIR on Android devices, you can resort to classic profiling solutions. Check the Android system tracing overview doc. Beside systrace, perfetto and the Android studio profile, also note that Inferno makes it easy to get flamegraphs.

To profile the replayer using AGI itself, you can export a given replay into a standalone APK (using gapit export_replay -apk), and profile that replay-APK using AGI.

Unit tests

Unit testing is achieved with separate frameworks depending on the programming language, but they are all accessible with Bazel.

List tests

# List all tests
bazel query 'tests(//...)'

# List all Go tests
bazel query 'kind(go_.*, tests(//...))'
# List all C++ tests
bazel query 'kind(cc_.*, tests(//...))'

Run tests

# Run all the tests
bazel test tests

# Run a given test
bazel test //core/log:go_default_test

Go

Following the regular Go test setup, tests are written as func TestXXX(t *testing.T) functions in *_test.go files.

Adding a Go test file into Bazel is done by invoking Gazelle. The kokoro/presubmit/presubmit.sh script does that for you: if you create or remove *_test.go files, running the presubmit script automatically edit the BUILD.bazel files to reflect your changes.

A few useful homemade packages:

github.com/google/gapid/core/assert defines an assertion framework.
github.com/google/gapid/core/log lets you create contexts for tests with ctx := log.Testing(t)

C++

TODO

Java

TODO

Code generated at compile time

A large amount of code is generated at compile time. Code is typically generated via APIC (API Compiler, cmd/apic/). APIC takes as input .api and .tmpl files, and it generates code in another language.


                    +----------+
  <.api files>  --->|          |
                    |   APIC   |---> <generated files>
  <.tmpl files> --->|          |
                    +----------+

.api files are GAPIL ("graphics API language") sources. GAPIL is a domain-specific language to specify a graphics API, it is documented in gapil/README.md. AGI currently supports only Vulkan, but its ancestor GAPID was designed to support arbitrary graphics APIs. Vulkan is described by API files located under gapis/api/vulkan/, the top-level file is gapis/api/vulkan/vulkan.api.

.tmpl files are template files. The templating language is documented in gapis/api/templates/README.md. There are various template files in the project to generate code for the interceptor, server, replayer, Vulkan layers, etc.

APIC is a GAPIL compiler, its entry-point is defined in cmd/apic/ and the actual compiler logic is defined in gapil/. In a nutshell, APIC parses the .api files to gather information about the graphics API, and then instantiates the templates in the .tmpl files to generate code.

Where does the generated code end up?

The generated code is not checked under version control. It is generated at compilation time by Bazel rules calling APIC, resulting in files that can be seen under e.g. bazel-bin/.

For instance, generated C++ code for the interceptor can be found in:

user@machine:~/work/agi$ find -L bazel-bin -name '*_spy_*.cpp'
bazel-bin/gapii/cc/vulkan_spy_0.cpp
bazel-bin/gapii/cc/vulkan_spy_subroutines_1.cpp
bazel-bin/gapii/cc/vulkan_spy_subroutines_0.cpp
bazel-bin/gapii/cc/vulkan_spy_2.cpp
bazel-bin/gapii/cc/vulkan_spy_3.cpp
bazel-bin/gapii/cc/vulkan_spy_helpers.cpp
bazel-bin/gapii/cc/vulkan_spy_1.cpp

To get a unified file tree view, interleaving source files with generated files, you can use the cmd/gofuse setup. cmd/gofuse links the generated source files in the same directories as their siblings in the same packages/namespaces.

Life of a gfxtrace

This is an overview of how AGI captures graphics API calls, stores them into a gfxtrace file, and process that file to replay the calls.

This is oriented to AGI developers who need to work with AGI internals. It is meant to help build a high-level mental model that facilitates navigating the actual source code. It references concepts and code modules that are unlikely to change anytime soon, and it tries not to reference details that are likely to change. You are encouraged to check the source code while reading this, to clarify how the various parts actually fit together. If you spot any discrepancy, please update this doc, but please keep it high-level.

AGI is architectured to be API-agnostic in order to support multiple graphics APIs. GAPID, from which AGI was forked, supports GLES and Vulkan. AGI's main focus is Vulkan on Android, so all examples in this doc are related to Vulkan on Android.

AGI's overall architecture

AGI is separated in main components that interact mostly via protobuf:

GAPIS (Graphics API Server, Go code under gapis/, see gapis/README.md) is the main component, running on the developer desktop/laptop. Any complex logic is meant to be implemented in GAPIS, while the other components are meant to be kept as simple as possible. The protobuf interface of GAPIS is defined in gapis/service/service.proto.
GAPII (Graphics API Interceptor, mostly C++ code under gapii/, see gapii/README.md) is the component responsible for intercepting graphics API calls during capture. It interacts with GAPIS via a dedicated protocol.
GAPIR (Graphics API Replayer, mostly C++ code under gapir/, see gapir/README.md) is the component that can replay graphics API calls. Its protobuf interface is defined in gapir/replay_service/service.proto.
GAPIC (Graphics API Client, Java code under gapic/, see gapic/README.md) is the GUI client. It uses GAPIS protobuf interface.
GAPIT (Graphics API Terminal, Go code under cmd/gapit/) is the developer-oriented CLI client. It uses GAPIS protobuf interface.

When you start AGI via the desktop icon or the ./agi command, this triggers the entry point defined under cmd/agi/, which by default starts a new GAPIS and then a new GAPIC that connects to this GAPIS. GAPIS may then itself start GAPII or GAPIR instances.

To capture and replay on Android, AGI has APKs (one per ABI, e.g. gapid-arm64-v8a.apk) that embeds GAPII and GAPIR.

Create a gfxtrace: capture, serialize and store Vulkan calls

AGI uses a Vulkan layer to intercept and capture the Vulkan calls emitted by an application, and stores them into a gfxtrace file. Be aware that in the code base, the act of intercepting graphics API calls may be referred by the words "capture", "trace", "intercept" and "spy".

For a Vulkan capture on Android, the main steps are:

GAPIS issues a few adb commands to edit global settings that tell the Android Vulkan loader to insert AGI's Vulkan layer when starting the app to capture. This layer is called GraphicsSpy and is implemented by libVkLayer_GraphicsSpy.so which is mostly a wrapper around libgapii.so.
The capture layer and GAPIS establish a TCP connection over ADB. The gapii::Spy::Spy() creator contains the logic to establish this connection.
The capture layer monitors every Vulkan API call, and shadows the Vulkan state accordingly. The logic of each Vulkan command is implemented in .api files under gapis/api/vulkan/, and code is auto-generated from these files (see Code generated at compile time). In particular, each command has a mutate function that mutates (updates) the Vulkan state with respect to the command logic. For instance, vkCreateBuffer() mutation results in adding a new buffer in the Vulkan state.
When the user clicks "Start" to start the one-frame capture, GAPIS tells the capture layer that it wants the next frame to be captured. The capture layer waits for the current frame to end before streaming the whole Vulkan state back to GAPIS (see e.g. VulkanSpy::serializeGPUBuffers). After that, each new intercepted Vulkan command and related memory observations are streamed to GAPIS. When the frame terminates, the capture layer sends a special "end" message to GAPIS.
GAPIS receives the serialized data from the capture layer and stores it into a gfxtrace file, until it receives the special "end" message.

What's in a gfxtrace file?

A gfxtrace file contains data encoded in proto-pack, a homemade format to encapsulate protobuf messages.

To see the plain content of a gfxtrace, you can use the ./gapit unpack -verbose myfile.gfxtrace command. On a simple Vulkan app, this produces the following (here edited to fit, and with added # comments):

# Header
Object(msg: Headerᵈ{ABI: ABIᵈ{OS: 4, architecture: 1, ...})
# API state at the start of the capture
BeginGroup(msg: GlobalStateᵈ{...}, id: 24)
Object(msg: Resourceᵈ{index: 1})
  ChildObject(msg: Observationᵈ{pool: 3, res_index: 1}, parentID: 24)
[...]
EndGroup(id: 24)
# List of commands
[...]
# Example of a command: vkQueueSubmit
## The command and its arguments
BeginGroup(msg: vkQueueSubmitᵈ{fence: 3916257488, pSubmits: 3141568848, ...}, id: 599)
## A few memory observations (resource + observation)
Object(msg: Resourceᵈ{data: [4 0 0 0 0 0 0 0 1 0 0 0 208 ...] (truncated 40 bytes), index: 12})
  ChildObject(msg: Observationᵈ{base: 3141568848, res_index: 12, size: 40}, parentID: 599)
Object(msg: Resourceᵈ{data: [240 87 109 233 0 0 0 0 176 110 109 233 0 0 0 0], index: 13})
  ChildObject(msg: Observationᵈ{base: 3838428368, res_index: 13, size: 16}, parentID: 599)
Object(msg: Resourceᵈ{data: [112 38 139 233], index: 14})
  ChildObject(msg: Observationᵈ{base: 3918206552, res_index: 14, size: 4}, parentID: 599)
## The actual call to the driver, and the return value (not being printed here as it is 0 == VK_SUCCESS)
  ChildObject(msg: vkQueueSubmitCallᵈ{}, parentID: 599)
EndGroup(id: 599)
[...]

At the proto-pack level, we have Object, ChildObject, BeginGroup and EndGroup. The msg fields are the protobuf messages. For instance, the Header protobuf message is defined in gapis/capture/capture.proto. The Vulkan-specific protobuf messages are defined in the api.proto file which is generated from the .api files.

We can see the capture header followed by GlobalState, the dump of Vulkan state. Then, the rest of the capture is made of a series of Vulkan calls. Each call is represented as a protopack group. This example illustrates how a vkQueueSubmit call is encoded.

In general, the call to a graphics API command leads to objects and messages that represent:

The API command and its arguments.
Zero or more memory observations that represent memory that the driver may read during this command. For instance, many Vulkan commands have pointers to struct as arguments: the content of these structures is read by the driver.
The actual call to the driver, and its return value (if any).
Zero or more memory observations that represent memory that the driver may have written to during its processing of the command. For instance, a vkCreateBuffer call writes the handle of the newly create buffer to the memory pointed at by its VkBuffer* pBuffer argument.

Note that on multithreaded apps, the object groups may be interleaved.

GAPIS handling of a gfxtrace

GAPIS parses gfxtrace files and represents them in a GraphicsCapture Go object. This type gives access to the header, the initial state and the list of commands, among other things. Once a gfxtrace file is loaded inside GAPIS, the clients can use GAPIS protobuf interface to interact with the capture.

For instance, a client may request the Vulkan state after a certain command. To obtain this state, GAPIS will use the Go version of the mutate functions (generated from the .api files) to mutate the initial state up to the required command, and return the resulting state. Note that this does not require a proper replay, as the state mutation happens entirely in GAPIS.

The .api files can be seen here as an implementation of a driver for a given graphics API, as they describe how each command affects the graphics API state. Thus, it is possible to simulate the evolution of the graphics API state inside GAPIS. This is what enables GAPIS to provide a snapshot of the state at some point in the capture without having to do an actual replay.

However, this driver simulation is not complete: the actual effects of draw calls to their render targets are not implemented. This means that while GAPIS does not need a replay to say e.g. how many images are in the state at a given point, it does need a replay to show you the content of such images after some draw calls. This replay is necessary as the result depends on the actual device and driver used for replay.

Replay of a gfxtrace

GAPIR is effectively a stack-based virtual machine specialized for the replay of graphics API commands, see details in its own README. To replay a gfxtrace, GAPIS takes a GraphicsCapture object and generates a payload made of GAPIR VM opcodes.

The actual transformation of API commands into replay opcodes is made by the mutate function of each command. These functions take a "replay builder" (see gapis/replay/builder module) as an optional argument. When this builder is not nil, the mutate function uses it to generate the replay opcodes corresponding to the API command.

When the initial state of a capture is not empty, GAPIS also generates "initial" commands that are required to reconstruct the initial state from a fresh empty state. For instance, if the initial state of a Vulkan capture has a Vulkan instance, GAPIS generates a vkCreateInstance command to recreate a similar instance. These initial commands must be replayed first in order to obtain a state from wich the capture commands can be called.

The command transformation framework

One of the key feature of AGI is being able to replay variations of the original capture. For instance, in order to see what the framebuffer looks like after a certain draw call, AGI must make a replay up to the desired draw call, but no further. In Vulkan, this typically requires to re-write the content of a command buffer to only include the relevant draw calls.

In order to implement such modifications on the capture, GAPIS has a command transformation framework. Conceptually, the commands of a capture are streamed into a chain of "transforms". A transform receives commands, may modify them, and then pass the resulting commands to the next transform. At the end of the chain, the obtained commands are mutated with a replay builder to obtain replay opcodes.

At a high-level, this can be compared to a series of unix pipes:

cat commands | transform1 | transform2 | ... | replay_builder > replay_payload

To see examples of Vulkan transforms, look at gapis/api/vulkan/transform_*.go files.

GAPIR executes the replay instructions

GAPIS uses the GAPIR protobuf service (gapir/replay_service/service.proto) to request the replay of a payload. This payload contains replay opcodes, and references to the required replay resources (i.e. the raw bytes of e.g. buffer contents).

The resources are not directly embedded in the replay payload: GAPIR lazily requests them to GAPIS during the replay. On Android, GAPIR runs on the device and communicates with GAPIS over ADB. Pushing the resources from GAPIS to GAPIR is very slow, as they must be transferred over ADB. Because a replay may not require all resources, and also because all resources may not fit in the replay device memory, AGI refrains from uploading all resources upfront. Instead, GAPIR maintains a resource cache and has some logic to request batches of resources to lower the number of requests while keeping the cache full.

During the replay, GAPIR can send back various information to GAPIS. For instance, it can send back the content of a render target at a given point. It also regularly sends notifications of how many instructions have been processed so far, this information is used to reflect the progress of a replay in GAPIC.

Split-replay: pre-warm replay with initial commands

In order to speed-up replays, GAPIS requests the initial commands of a capture to be replayed even before the user asks for a replay.

Depending on the replay request, the capture commands may be transformed to produce a relevant replay payload. Most of the time, these transformations only need to be applied on the capture commands, not on the initial commands. Hence, when waiting for user input, it makes sense to replay the default initial commands to rebuilt the initial state: once the user requests a specific replay, only the (transformed) capture commands needs to be replayed.

If the user-requested replay does require to transform the initial commands, then the pre-warm replay is abandonned and a new replay of the transformed initial and capture commands is executed.

Life of a perfetto trace (system profile trace)

AGI heavily relies on the perfetto system profiling framework to obtain, store and process profiling data. Hence we often refer to system profile traces as "perfetto traces". If you have to deal with perfetto code, make sure to refer to the perfetto documentation.

Perfetto is built into Android since Android 9 Pie. In general, to take a perfetto trace, you can use the perfetto command-line tool on the device. See perfetto's web interface at https://ui.perfetto.dev/ and click on "Recording command" to see an example of how the perfetto command-line tool can be used to obtain a profiling trace.

To take a trace, AGI may use either the perfetto command-line tool, or perfetto's client interface. See e.g. gapis/perfetto/android/trace.go:Capture() for how a capture is started on Android. To see an example of AGI using perfetto's command line interface, see core/os/android/adb/perfetto.go:StartPerfettoTrace(). Alternatively, AGI may interact via perfetto's client interface by talking to the traced deamon running on the device. This deamon listens to the /dev/socket/traced_consumer, and AGI connects directly to this socket. The related AGI code is under gapis/perfetto/client/.

One specificity of GPU profiling is that some of the perfetto data producers are inside GPU drivers, and they need to be started before a trace with these GPU data sources can be taken. To start these GPU-specific perfetto data producers, AGI has a small agi_launch_producer utility (see source in cmd/launch_producer/). On Android, AGI extracts this utiliy from its own APK and invokes it, such that the relevant GPU data producers are started (see gapidapk/gapidapk.go:EnsurePerfettoProducerLaunched()).

Once a perfetto trace has been collected, AGI uses perfetto's trace processor to retrieve profiling data using SQL queries.

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