gperftools
Main gperftools repository (by gperftools)
gprof2dot
Converts profiling output to a dot graph. (by jrfonseca)
| gperftools | gprof2dot | |
|---|---|---|
| 4 | 5 | |
| 8,177 | 3,095 | |
| 0.9% | - | |
| 9.5 | 4.8 | |
| 25 days ago | about 2 months ago | |
| C++ | Python | |
| BSD 3-clause "New" or "Revised" License | GNU Lesser General Public License v3.0 only |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
gperftools
Posts with mentions or reviews of gperftools.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-05-20.
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I find it's not possible to do serious C/C++ coding on latest macOS
For profiling you are right clang has no -pg that works. But there are options, since clang supports PGO the fprofile flags could be what you need. they will generated a profraw file for you. There is also gperf tools which work for more than just linux. https://github.com/gperftools/gperftools
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Why So Slow? Using Profilers to Pinpoint the Reasons of Performance Degradation
Because we couldn't identify the issue using the results we got from Callgrind, we reached for another profiler, gperftools. It's a sampling profiler and therefor it has a smaller impact on the application's performance in exchange for less accurate call statistics. After filtering out the unimportant parts and visualizing the rest with pprof, it was evident that something strange was happening with the send function. It took only 71 milliseconds with the previous implementation and more than 900 milliseconds with the new implementation of our Bolt server. It was very suspicious, but based on Callgrind, its cost was almost the same as before. We were confused as the two results seemed to conflict with each other.
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Is there a way I can visualize all the function calls made while running the project(C++) in a graphical way?
gprftools (https://github.com/gperftools/gperftools) can be easily plugged in using LD_PRELOAD and signal, and has nice go implemented visualization tool https://github.com/google/pprof.
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How do applications request for RAM from the CPU?
Google's tcmalloc
gprof2dot
Posts with mentions or reviews of gprof2dot.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-01-30.
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Visualizing Pythons process?
It also lets you run tools like https://github.com/jrfonseca/gprof2dot on the profiling results to generate comprehensive flowcharts (call graph) for your program.
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Map a python project
The closes thing I can think of is gprof2dot. It's used for visual representations after profiling code: https://github.com/jrfonseca/gprof2dot
- Scanning Function calls in a script - is there a tool?
- Is there a way I can visualize all the function calls made while running the project(C++) in a graphical way?
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Profiling Flask application to improve performance
There are a few tools to visualise the profile dumps. Some of them providing a full GUI for navigatig within your profiling results ( RunSnakeRun), some of them represent the analysis result as a Graph (gprof2dot). I stopped on snakeviz, which is a browser based visualizer. It is easy installed using pip install snakeviz, and then simply run with snakeviz profile_dir. The result looks something like this, and you can dive in to each of the visual parts to see its more close detalization, which is in my opinion is super cool and handy.
What are some alternatives?
When comparing gperftools and gprof2dot you can also consider the following projects:
pprof - pprof is a tool for visualization and analysis of profiling data
tracy - Frame profiler
jemalloc
flask-profiler - a flask profiler which watches endpoint calls and tries to make some analysis.
massif-visualizer - Visualizer for Valgrind Massif data files
mimalloc - mimalloc is a compact general purpose allocator with excellent performance.
pytest-austin - Python Performance Testing with Austin
minitrace - Simple C/C++ library for producing JSON traces suitable for Chrome's built-in trace viewer (about:tracing).
SnakeViz - An in-browser Python profile viewer