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84 lines
2.6 KiB
ReStructuredText
84 lines
2.6 KiB
ReStructuredText
Profiling (internal)
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====================
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This document details, for Ray developers, how to analyze Ray performance.
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Getting a stack trace of Ray C++ processes
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------------------------------------------
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You can use the following GDB command to view the current stack trace of any
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running Ray process (e.g., raylet). This can be useful for debugging 100% CPU
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utilization or infinite loops (simply run the command a few times to see what
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the process is stuck on).
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.. code-block:: shell
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sudo gdb -batch -ex "thread apply all bt" -p <pid>
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Note that you can find the pid of the raylet with ``pgrep raylet``.
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Installation
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------------
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These instructions are for Ubuntu only. Attempts to get ``pprof`` to correctly
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symbolize on Mac OS have failed.
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.. code-block:: bash
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sudo apt-get install google-perftools libgoogle-perftools-dev
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Launching the to-profile binary
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-------------------------------
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If you want to launch Ray in profiling mode, define the following variables:
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.. code-block:: bash
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export RAYLET_PERFTOOLS_PATH=/usr/lib/x86_64-linux-gnu/libprofiler.so
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export RAYLET_PERFTOOLS_LOGFILE=/tmp/pprof.out
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The file ``/tmp/pprof.out`` will be empty until you let the binary run the
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target workload for a while and then ``kill`` it via ``ray stop`` or by
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letting the driver exit.
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Visualizing the CPU profile
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---------------------------
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The output of ``pprof`` can be visualized in many ways. Here we output it as a
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zoomable ``.svg`` image displaying the call graph annotated with hot paths.
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.. code-block:: bash
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# Use the appropriate path.
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RAYLET=ray/python/ray/core/src/ray/raylet/raylet
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google-pprof -svg $RAYLET /tmp/pprof.out > /tmp/pprof.svg
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# Then open the .svg file with Chrome.
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# If you realize the call graph is too large, use -focus=<some function> to zoom
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# into subtrees.
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google-pprof -focus=epoll_wait -svg $RAYLET /tmp/pprof.out > /tmp/pprof.svg
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Here's a snapshot of an example svg output, taken from the official
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documentation:
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.. image:: http://goog-perftools.sourceforge.net/doc/pprof-test-big.gif
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Running Microbenchmarks
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-----------------------
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To run a set of single-node Ray microbenchmarks, use:
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.. code-block:: bash
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ray microbenchmark
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You can find the microbenchmark results for Ray releases in the `GitHub release logs <https://github.com/ray-project/ray/tree/master/release/release_logs>`__.
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References
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----------
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- The `pprof documentation <http://goog-perftools.sourceforge.net/doc/cpu_profiler.html>`_.
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- A `Go version of pprof <https://github.com/google/pprof>`_.
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- The `gperftools <https://github.com/gperftools/gperftools>`_, including libprofiler, tcmalloc, and other goodies.
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