swri_profiler repository

Repository Summary

Checkout URI https://github.com/swri-robotics/swri_profiler.git
VCS Type git
VCS Version kinetic-devel
Last Updated 2018-11-09
Dev Status DEVELOPED
Released RELEASED

Packages

Name Version
swri_profiler 0.1.0
swri_profiler_msgs 0.1.0
swri_profiler_tools 0.1.0

README

swri_profiler

Swri_profiler is a lightweight profiling framework for C++ ROS nodes. It allows you to selectively measure how much time is spent in various scopes. Profiling data is generated and published to a ROS topic where it can be recorded or monitored in real time. The profiler was designed to be lightweight enough that it can be left in during normal operation so that performance data can be monitored at any time.

Getting Started

Add swri_profiler to your ROS workspace, update the workspace to clone your repository, and build swri_profiler with catkin.

Once built, you can test that everything was installed properly with the built in test nodes:

  1. Start a roscore

You can skip this step, but it's convenient to have a separate roscore running so you can start and stop the other launch files easily.

  1. Launch swri_profiler / testing_example.launch

As soon as the nodes are running, the profiler will begin collecting profiling data and publishing it. You can verify that the profiler is working by watching the /profiler/data and /profiler/index topics.

  1. Launch swri_profiler / profiler.launch

The profile viewer is implemented as a webpage with javascript. This launch file starts up roslibjs rosbridge_server and runs a lightweight Python server to server the webpage. (Be aware that the Python server will serve pages to any clients.)

  1. Point a web browser to http://localhost:8000/

The viewer is useful but still in a very preliminary state. If you see some colorful but boring plots this point, that means everything is working.

Using the profiler

Adding the profiler to a node is very straightforward:

  1. Add swri_profiler as a dependency to your package.

  2. Include swri_profiler/profiler.h in files that you want to profile.

  3. Call the macro SWRI_PROFILE("my-label") at the start of any scope that you want to profile.

SWRI_PROFILE creates a local variable with a unique name at the point where it is called. The local variable records the time when it was created. When the variable goes out of scope, the end time is recorded to get the running time of your code.

That's all it takes to get started. The profiler will automatically initialize itself when it is first used, and automatically close itself when the ROS node is shutdown.

Profile Stack

The profiler is aware of all currently running profiles. When a new profile is started, it becomes a child of the profile that it is running in. This allows the profiler to report the results as a call tree. The tree is defined by where you place calls to SWRI_PROFILE rather than the actual call stack. This allows you to selectively collect as detailed or broad of a profile as you want.

Consider this simple example:

void handleOdometry(...)
{
    SWRI_PROFILE("handle-odometry");

    runStateEstimator();
    publishOutput();
}

void runStateEstimator(...)
{
    SWRI_PROFILE("run-state-estimator");
    /* do some work... */
}

void publishOutput(...)
{
    SWRI_PROFILE("publish-output");
    /* do some work... */
}

This code will result in three distinct items in the profiler:

  • handle-odometry
  • handle-odometry/run-state-estimator
  • handle-odometry/publish-output

The profiler viewer can use this data to estimate the inclusive and exclusive time spent in each block. This is extremely convenient because the tree is generated automatically without any extra work from you.

Tips

  1. Like ROS, Swri_profiler uses the forward slash "/" to distinguish namespaces. Avoid using "/" in your profiler labels unless you know what you're doing. The profiler won't care, but it can cause confusing output.

  2. Add a profile to every ROS callback in your node:

SWRI_PROFILE(ros::this_node::getName());

Tracking every callback allows you to get a complete picture of how much time is spent in the node, and allows you to compare the time spent between different nodes. The name returned by ROS will include the nodes namespace, allowing you to also measure how much (instrumented) time is spent in a given namespace and compare the loading between namespaces.

If you also want to track a callback individually, just tack on another SWRI_PROFILE:

SWRI_PROFILE(ros::this_node::getName());
SWRI_PROFILE("callback-label");

Repository Summary

Checkout URI https://github.com/swri-robotics/swri_profiler.git
VCS Type git
VCS Version master
Last Updated 2018-11-09
Dev Status DEVELOPED
Released RELEASED

Packages

Name Version
swri_profiler 0.1.0
swri_profiler_msgs 0.1.0
swri_profiler_tools 0.1.0

README

swri_profiler

Swri_profiler is a lightweight profiling framework for C++ ROS nodes. It allows you to selectively measure how much time is spent in various scopes. Profiling data is generated and published to a ROS topic where it can be recorded or monitored in real time. The profiler was designed to be lightweight enough that it can be left in during normal operation so that performance data can be monitored at any time.

Getting Started

Add swri_profiler to your ROS workspace, update the workspace to clone your repository, and build swri_profiler with catkin.

Once built, you can test that everything was installed properly with the built in test nodes:

  1. Start a roscore

You can skip this step, but it's convenient to have a separate roscore running so you can start and stop the other launch files easily.

  1. Launch swri_profiler / testing_example.launch

As soon as the nodes are running, the profiler will begin collecting profiling data and publishing it. You can verify that the profiler is working by watching the /profiler/data and /profiler/index topics.

  1. Launch swri_profiler / profiler.launch

The profile viewer is implemented as a webpage with javascript. This launch file starts up roslibjs rosbridge_server and runs a lightweight Python server to server the webpage. (Be aware that the Python server will serve pages to any clients.)

  1. Point a web browser to http://localhost:8000/

The viewer is useful but still in a very preliminary state. If you see some colorful but boring plots this point, that means everything is working.

Using the profiler

Adding the profiler to a node is very straightforward:

  1. Add swri_profiler as a dependency to your package.

  2. Include swri_profiler/profiler.h in files that you want to profile.

  3. Call the macro SWRI_PROFILE("my-label") at the start of any scope that you want to profile.

SWRI_PROFILE creates a local variable with a unique name at the point where it is called. The local variable records the time when it was created. When the variable goes out of scope, the end time is recorded to get the running time of your code.

That's all it takes to get started. The profiler will automatically initialize itself when it is first used, and automatically close itself when the ROS node is shutdown.

Profile Stack

The profiler is aware of all currently running profiles. When a new profile is started, it becomes a child of the profile that it is running in. This allows the profiler to report the results as a call tree. The tree is defined by where you place calls to SWRI_PROFILE rather than the actual call stack. This allows you to selectively collect as detailed or broad of a profile as you want.

Consider this simple example:

void handleOdometry(...)
{
    SWRI_PROFILE("handle-odometry");

    runStateEstimator();
    publishOutput();
}

void runStateEstimator(...)
{
    SWRI_PROFILE("run-state-estimator");
    /* do some work... */
}

void publishOutput(...)
{
    SWRI_PROFILE("publish-output");
    /* do some work... */
}

This code will result in three distinct items in the profiler:

  • handle-odometry
  • handle-odometry/run-state-estimator
  • handle-odometry/publish-output

The profiler viewer can use this data to estimate the inclusive and exclusive time spent in each block. This is extremely convenient because the tree is generated automatically without any extra work from you.

Tips

  1. Like ROS, Swri_profiler uses the forward slash "/" to distinguish namespaces. Avoid using "/" in your profiler labels unless you know what you're doing. The profiler won't care, but it can cause confusing output.

  2. Add a profile to every ROS callback in your node:

SWRI_PROFILE(ros::this_node::getName());

Tracking every callback allows you to get a complete picture of how much time is spent in the node, and allows you to compare the time spent between different nodes. The name returned by ROS will include the nodes namespace, allowing you to also measure how much (instrumented) time is spent in a given namespace and compare the loading between namespaces.

If you also want to track a callback individually, just tack on another SWRI_PROFILE:

SWRI_PROFILE(ros::this_node::getName());
SWRI_PROFILE("callback-label");