Heap Profiling with MemoryInfra

As of Chrome 48, MemoryInfra supports heap profiling. The core principle is a solution that JustWorks™ on all platforms without patching or rebuilding, integrated with the chrome://tracing ecosystem.

How to Use

  1. Start Chrome with the --enable-heap-profiling switch. This will make Chrome keep track of all allocations.

  2. Grab a MemoryInfra trace. For best results, start tracing first, and then open a new tab that you want to trace. Furthermore, enabling more categories (besides memory-infra) will yield more detailed information in the heap profiler backtraces.

  3. When the trace has been collected, select a heavy memory dump indicated by a purple M dot. Heap dumps are only included in heavy memory dumps.

  4. In the analysis view, cells marked with a triple bar icon (☰) contain heap dumps. Select such a cell.

    Cells containing a heap dump

  5. Scroll down all the way to Heap Details.

  6. Pinpoint the memory bug and live happily ever after.

Native stack traces

By default heap profiling collects pseudo allocation traces, which are based on trace events. I.e. frames in allocation traces correspond to trace events that were active at the time of allocations, and are not real function names. It's also possible to use heap profiling with native, symbolized stack traces.

Native stack traces (Chrome - macOS/Windows)

  1. Using any officially distributed build of Chrome, navigate to chrome://flags, and set “enable-heap-profiling” to Enabled (native mode).

  2. Use the TraceOnTap extension to grab a trace.

  3. Run the following script to symbolize the trace.

     third_party/catapult/tracing/bin/symbolize_trace <trace file>
  4. Load the trace file in chrome://tracing. Locate a purple M dot, and continue from step 3 from the instructions above. Native stack traces will be shown in the Heap Details pane.

Native stack traces (Chromium - all OSes)

On Linux / Android, you need to build Chromium with special flags to use native heap profiling. On macOS / Windows, it's also possible to use native heap profiling with Chromium.

  1. Build with the following GN flags:

    macOS / Windows

    symbol_level = 1


    enable_profiling = true
    symbol_level = 1


    arm_use_thumb = false
    enable_profiling = true
    symbol_level = 1
  1. Start Chrome with --enable-heap-profiling=native switch (notice =native part).

    On Android use the command line tool before starting the app:

    build/android/adb_chrome_public_command_line --enable-heap-profiling=native

    (run the tool with an empty argument '' to clear the command line)

  2. Grab a MemoryInfra trace. You don't need any other categories besides memory-infra.

  3. Save the grabbed trace file. This step is needed because freshly taken trace file contains raw addresses (which look like pc:dcf5dbf8) instead of function names, and needs to be symbolized.

  4. Symbolize the trace file. During symbolization addresses are resolved to the corresponding function names and trace file is rewritten (but a backup is saved with .BACKUP extension).


    third_party/catapult/tracing/bin/symbolize_trace <trace file>


    third_party/catapult/tracing/bin/symbolize_trace --output-directory out/Release <trace file>

    (note --output-directory and make sure it's right for your setup)

  5. Load the trace file in chrome://tracing. Locate a purple M dot, and continue from step 3 from the instructions above. Native stack traces will be shown in the Heap Details pane.

Heap Details

The heap details view contains a tree that represents the heap. The size of the root node corresponds to the selected allocator cell.

The size value in the heap details view will not match the value in the selected analysis view cell exactly. There are three reasons for this. First, the heap profiler reports the memory that the program requested, whereas the allocator reports the memory that it actually allocated plus its own bookkeeping overhead. Second, allocations that happen early --- before Chrome knows that heap profiling is enabled --- are not captured by the heap profiler, but they are reported by the allocator. Third, tracing overhead is not discounted by the heap profiler.

The heap can be broken down in two ways: by backtrace (marked with an ƒ), and by type (marked with a Ⓣ). When tracing is enabled, Chrome records trace events, most of which appear in the flame chart in timeline view. At every point in time these trace events form a pseudo stack, and a vertical slice through the flame chart is like a backtrace. This corresponds to the ƒ nodes in the heap details view. Hence enabling more tracing categories will give a more detailed breakdown of the heap.

The other way to break down the heap is by object type. At the moment this is only supported for PartitionAlloc.

In official builds, only the most common type names are included due to binary size concerns. Development builds have full type information.

To keep the trace log small, uninteresting information is omitted from heap dumps. The long tail of small nodes is not dumped, but grouped in an <other> node instead. Note that although these small nodes are insignificant on their own, together they can be responsible for a significant portion of the heap. The <other> node is large in that case.


In the trace below, ParseAuthorStyleSheet is called at some point.

ParseAuthorStyleSheet pseudo stack

The pseudo stack of trace events corresponds to the tree of ƒ nodes below. Of the 23.5 MiB of memory allocated with PartitionAlloc, 1.9 MiB was allocated inside ParseAuthorStyleSheet, either directly, or at a deeper level (like CSSParserImpl::parseStyleSheet).

Memory Allocated in ParseAuthorStyleSheet

By expanding ParseAuthorStyleSheet, we can see which types were allocated there. Of the 1.9 MiB, 371 KiB was spent on ImmutableStylePropertySets, and 238 KiB was spent on StringImpls.

ParseAuthorStyleSheet broken down by type

It is also possible to break down by type first, and then by backtrace. Below we see that of the 23.5 MiB allocated with PartitionAlloc, 1 MiB is spent on Nodes, and about half of the memory spent on nodes was allocated in HTMLDocumentParser.

The PartitionAlloc heap broken down by type first and then by backtrace

Heap dump diffs are fully supported by trace viewer. Select a heavy memory dump (a purple dot), then with the control key select a heavy memory dump earlier in time. Below is a diff of theverge.com before and in the middle of loading ads. We can see that 4 MiB were allocated when parsing the documents in all those iframes, almost a megabyte of which was due to JavaScript. (Note that this is memory allocated by PartitionAlloc alone, the total renderer memory increase was around 72 MiB.)

Diff of The Verge before and after loading ads