# Memory Benchmarks
This document describes benchmarks available to track Chrome's and
WebView's memory usage, where they live, what they measure, how to run them,
and on how to diagnose regressions.
[TOC]
## Glossary
* **User story:** a set of actions to perform on a browser or device (e.g.
open google homepage, type "foo", click search, scroll down, visit first
result, etc.).
* **Metric:** a data aggregation process that takes a Chrome trace as input
(produced by a [Telemetry][] run) and produces a set of summary numbers as
output (e.g. total GPU memory used).
* **Benchmark:** a combination of (one or more) user stories and (one or
more) metrics.
[Telemetry]: https://github.com/catapult-project/catapult/blob/master/telemetry/README.md
## System Health
*System health* is an effort to unify top-level benchmarks (as opposite to
micro-benchmarks and regression tests) that are suitable to capture
representative user stories.
### Benchmarks
System health memory benchmarks are:
* [system_health.memory_mobile][system_health] -
user stories running on Android devices.
* [system_health.memory_desktop][system_health] -
user stories running on desktop platforms.
These benchmarks are run continuously on the [chrome.perf][] waterfall,
collecting and reporting results on the
[Chrome Performance Dashboard][chromeperf].
[system_health]: https://chromium.googlesource.com/chromium/src/+/main/tools/perf/page_sets/system_health/
[chrome.perf]: https://ci.chromium.org/p/chrome/g/chrome.perf/console
[chromeperf]: https://chromeperf.appspot.com/report
### User stories
System health user stories are classified by the kind of interactions they
perform with the browser:
* `browse` stories navigate to a URL and interact with the page; e.g.
scroll, click on elements, navigate to subpages, navigate back.
* `load` stories just navigate to a URL and wait for the page to
load.
* `background` stories navigate to a URL, possibly interact with the
page, and then bring another app to the foreground (thus pushing the
browser to the background).
* `long_running` stories interact with a page for a longer period
of time (~5 mins).
* `multitab` loads different web sites in several tabs, then cycles through
them.
* `play` loads a web site and plays some media (e.g. a song).
The full name of a story has the form `{interaction}:{category}:{site}[:{year}]`
where:
* `interaction` is one the labels given above;
* `category` is used to group together sites with a similar purpose,
e.g. `news`, `social`, `tools`;
* `site` is a short name identifying the website in which the story mostly
takes place, e.g. `cnn`, `facebook`, `gmail`.
* `year` indicates the year in which the web page recording for the story
was most recently updated.
For example `browse:news:cnn:2018` and `background:social:facebook` are two
system health user stories. The list of all current stories can be found at
[bit.ly/csh-stories](http://bit.ly/csh-stories).
Today, for most stories, a garbage collection is forced at the end of the
story and a memory dump is then triggered. Metrics report the values
obtained from this single measurement.
## Continuous monitoring
To view data from one of the benchmarks on the
[Chrome Performance Dashboard][chromeperf] you should select:
* **Test suite:** The name of a *[benchmark](#Benchmarks)*.
* **Bot:** The name of a *platform or device configuration*. Sign in to also
see internal bots.
* **Subtest (1):** The name of a *[metric](#Understanding-memory-metrics)*.
* **Subtest (2):** The name of a *story group*; these have the form
`{interaction}_{category}` for system health stories.
* **Subtest (3):** The name of a *[user story](#User-stories)*
(with `:` replaced by `_`).
Clicking on any point of the graph will give you the commit range, links to the
builder that ran the benchmark, and a trace file collected during the story
run. See below for details on how to interpret these traces when
[debugging memory related issues](#debugging-memory-regressions).
Many of the high level memory measurements are automatically tracked and the
Performance Dashboard will generate alerts when a memory regression is detected.
These are triaged by [perf sheriffs][] who create bugs and start bisect jobs
to find the root cause of regressions.
[perf sheriffs]: /docs/speed/perf_regression_sheriffing.md
## Debugging memory regressions
If you are investigating a memory regression, chances are, a [pinpoint][]
job identified one of your CLs as a possible culprit.
Note the "chart" argument identifies the memory metric that regressed. The
pinpoint results page also gives you easy access to traces before and after
your commit landed. It's useful to look at both and compare them to identify what
changed. The documentation on [memory-infra][memory-infra] explains how to dig
down into details and interpret memory measurements. Also note that pinpoint
runs each commit multiple times, so you can access more traces by clicking on
a different "repeat" of either commit.
Sometimes it's also useful to follow the link to "Analyze benchmark results"
which will bring up the [Metrics Results UI][results-ui] to compare all
measurements (not just the one caught by the alert) before and after your
CL landed. Make sure to select the "before" commit as reference column, show
absolute changes (i.e. "Δavg") instead of relative, and sort by the column
with changes on the "after" commit to visualize them more easily. This can be
useful to find a more specific source of the regression, e.g.
`renderer_processes:reported_by_chrome:v8:heap:code_space:effective_size`
rather than just `all_processes:reported_by_chrome:effective_size`, and help
you pin down the source of the regression.
To confirm whether a revert of your CL would fix the regression you can run
a [pinpoint try job](#How-to-run-a-pinpoint-try-job) with a patch containing
the revert. Finally, **do not close the bug** even if you suspect that your CL
may not be the cause of the regression; instead follow the more general
guidance on how to [address performance regressions][addressing-regressions].
Bugs should only be closed if the regression has been fixed or justified.
[results-ui]: https://chromium.googlesource.com/catapult.git/+/HEAD/docs/metrics-results-ui.md
[memory-infra]: /docs/memory-infra/README.md
[addressing-regressions]: /docs/speed/addressing_performance_regressions.md
## How to run the benchmarks
Benchmarks may be run on a local platform/device or remotely on a pinpoint
try job.
### How to run a pinpoint try job
Given a patch already uploaded to code review, try jobs provide a convenient
way to evaluate its memory implications on devices or platforms which
may not be immediately available to developers.
To start a try job go to the [pinpoint][] website, click on the `+` button to
create a new job, and fill in the required details:
[pinpoint]: https://pinpoint-dot-chromeperf.appspot.com/
* **Bug ID** (optional): The id of a crbug.com issue where pinpoint can post
updates when the job finishes.
* **Gerrit URL**: URL to the patch you want to test. Note that your patch can
live in chromium or any of its sub-repositories!
* **Bot**: Select a suitable device/platform from the drop-down menu on which
to run your job.
* **Benchmark**: The name of the benchmark to run. If you are interested in
memory try `system_health.memory_mobile` or `system_health.memory_desktop`
as appropriate.
* **Story** (optional): A pattern (Python regular expression) passed to
Telemetry's `--story-filter` option to only run stories that match the
pattern.
* **Extra Test Arguments** (optional): Additional command line arguments for
Telemetry's `run_benchmark`. Of note, if you are interested in running a
small but representative sample of system health stories you can pass
`--story-tag-filter health_check`.
If you have more specific needs, or need to automate the creation of jobs, you
can also consider using [pinpoint_cli][].
[pinpoint_cli]: https://cs.chromium.org/chromium/src/tools/perf/pinpoint_cli
### How to run locally
After building, e.g. `ChromePublic.apk`, you can run a specific system health
story with the command:
```
$SRC/tools/perf/run_benchmark run system_health.memory_mobile \
--browser android-chromium --story-filter load:search:google
```
This will run the story with a default of 3 repetitions and produce a
`results.html` file comparing results from this and any previous benchmark
runs. In addition, you'll also get individual [trace files][memory-infra]
for each story run by the benchmark. **Note:** by default only high level
metrics are shown, you may need to tick the "Show all" check box in order to
view some of the lower level memory metrics.
Other useful options for this command are:
* `--pageset-repeat [n]` - override the default number of repetitions
* `--reset-results` - clear results from any previous benchmark runs in the
`results.html` file.
* `--results-label [label]` - give meaningful names to your benchmark runs,
this way it is easier to compare them.
For WebView make sure to [replace the system WebView][webview_install]
on your device and use `--browser android-webview`.
[memory-infra]: /docs/memory-infra/README.md
[webview_install]: https://www.chromium.org/developers/how-tos/build-instructions-android-webview
## Understanding memory metrics
There is a large number of [memory-infra][] metrics, breaking down usage
attributed to different components and processes.
Most memory metrics have the form
`memory:{browser}:{processes}:{source}:{component}:{kind}`
where:
* **browser:** One of `chrome` or `webview`.
* **processess:** One of `browser_process`, `renderer_processess`,
`gpu_process`, or `all_processess`.
* **source:** One of `reported_by_chrome` or `reported_by_os`
* **component:** May be a Chrome component, e.g. `skia` or `sqlite`;
details about a specific component, e.g. `v8:heap`; or a class of memory
as seen by the OS, e.g. `system_memory:native_heap` or `gpu_memory`. If
reported by chrome, the metrics are gathered by `MemoryDumpProvider`s,
probes placed in the specific components' codebase. For example, in
"memory:chrome:all_processes:reported_by_chrome:net:effective_size_avg,"
the component is "net" which is Chrome's network stack and
"reported_by_chrome" means that this metric is gathered via probes in
the network stack.
* **kind:** The kind of memory being reported. For metrics reported by
Chrome this usually is `effective_size` (others are `locked_size`
and `allocated_objects_size`); for metrics by the OS this usually is
`proportional_resident_size` (others are `peak_resident_size` and
`private_dirty_size`).
Read the [memory-infra documentation][memory-infra] for more details on them.
[memory-infra]: /docs/memory-infra/README.md
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