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Linux Scheduling Visualization

Build and Test SchedViz

This is not an officially supported Google product.

SchedViz is a tool for gathering and visualizing kernel scheduling traces on Linux machines. It helps to:

  • quantify task starvation due to round-robin queueing,
  • identify primary antagonists stealing work from critical threads,
  • determine when core allocation choices yield unnecessary waiting,
  • evaluate different scheduling policies,
  • and much more.

To learn more about what SchedViz can do and what problems it can solve, read our announcement post on the Google open source blog.

Running SchedViz

To get started clone this repo:

git clone https://github.com/google/schedviz.git

SchedViz requires yarn. Closely follow the installation instructions on the yarn Website. Make sure you have a recent version of Node.js (>= 10.9.0) installed as well.

Building SchedViz also requires the GNU build tools and the unzip utility. On Debian, for example, the dependencies can be installed by executing this command:

sudo apt-get update && sudo apt-get install build-essential unzip

To run SchedViz, run the following commands:

cd schedviz # The location where the repo was cloned
yarn install

Once yarn has finished run the following command in the root of the repo to start the server:

yarn bazel run server -- -- -storage_path="Path to a folder to store traces in"

The server binary takes several options:

Name Type Description
storage_path String Required.
The folder where trace data is/will
: : : be stored.
This should be an empty folder that :
: : : is not used by anything else. :
cache_size Int Optional.
The maximum number of collections to
: : : keep open in memory at once. :
port Int Optional.
The port to run the server
: : : on.
Defaults to 7402. :
resources_root String Optional.
The folder where the static files
: : : (e.g. HTML and JavaScript) are stored.
Default :
: : : is "client".
If using bazel to run the server, :
: : : you shouldn't need to change this. :

To load SchedViz, go to http://localhost:7402/collections

Manually collecting a scheduling trace

  1. Run the trace.sh as root on the machine that you want to collect a trace from:

    sudo ./trace.sh -out 'Path to directory to save trace in' \
                    -capture_seconds 'Number of seconds to record a trace' \
                    [-buffer_size 'Size of the trace buffer in KB'] \
                    [-copy_timeout 'Time to wait for copying to finish']

    Default number of seconds to wait for copy to finish is 5. The copying of the raw traces from Ftrace to the output file won't finish automatically as the raw trace pipes aren't closed. This setting is a timeout for when the copying should stop. It should be at least as long as it takes to copy out all the trace files. If you see incomplete traces, try increasing the timeout.

    Default buffer size is 4096 KB.

    The shell script collects the sched_switch, sched_wakeup, sched_wakeup_new, and sched_migrate_task tracepoints.

    NOTE: There is also a binary version of the trace collector script, which can collect traces larger than the size of the buffer.

    To build it, run bazel build util:trace from the root of the repo.

    To run it, run sudo bazel-bin/util/trace. It takes the same arguments as the shell script, except -copy_timeout.

  2. Copy the generated tar.gz file off of the trace machine to a machine that can access the SchedViz UI.

  3. Upload the output tar.gz file to SchedViz by clicking the "Upload Trace" button on the SchedViz collections page. The tar.gz file will be located at $OUTPUT_PATH/trace.tar.gz.

Collecting a scheduling trace on a GCE machine

Using gcloud you can easily collect a trace on a remote GCE machine. We've written a helper script to collect a trace on a GCE machine with a single command. This script is a wrapper around the manual trace script.

Usage: bash ./gcloud_trace.sh -instance 'GCE Instance Name' \ -trace_args 'Arguments to forward to trace script' \ [-project 'GCP Project Name'] \ [-zone 'GCP Project Zone'] \ [-script 'Path to trace script']

Analyzing a trace

Take a look at our features and usage walkthrough.

Keyboard Shortcuts

Key Description
? (Shift + /) Show a shortcut cheatsheet dialog
Shift + c Copy the current tooltip text to the clipboard
Shift + a Reset zoom level in heatmap viewport
Shift + x Clear the CPU filter

Common sources of errors

Errors collecting traces

  • When the trace takes longer to copy than the timeout passed to the trace collection script (default timeout is five seconds), traces will not be fully copied into the output file. To fix this, increase the copy timeout parameter to a larger and sufficient value.

  • If a CPU's trace buffer fills up before the timeout is reached, recording will be stopped for that CPU. Other CPUs may keep recording until their buffers fill up, but only the events occurring up to the last event in the first buffer to fill up will be used.

Errors loading traces

SchedViz infers CPU and thread state information that isn't directly attested in the trace, and fails aggressively when this inference does not succeed. In particular, two factors may increase the likelihood of inference failures: * PID reuse. Machines with small PID address spaces, or long traces, may experience PID reuse, where two separate threads are assigned the same PID. This can lead to inference failures, for example, threads last seen on one CPU could appear on another without an intervening migration. * Event ordering. Scheduling trace interpretation relies on an accurate total ordering between the scheduling events; event timestamps are generated by their emitting CPU's rdtsc. If the cores of a machine do not have their rdtscs tightly aligned, events may appear to slip, which can lead to inference errors as above.

Events can also have incorrect timestamps written if the kernel is interrupted while it is recording an event, and the interrupt tries to write another event. This will result in many events appearing having the same timestamp when they shouldn't. This type of error occurs when recording high-frequency events such as the workqueue family, and it very rarely occurs when recording only scheduling events.

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A tool for gathering and visualizing kernel scheduling traces on Linux machines

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