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fix links in release notes
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‎posts/2009/10/first-pypy-cli-jit-benchmarks-6698484455072589492.html

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course, things are improving very quickly so it should become more and more
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stable as days pass.</p>
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<p>For this time, I decided to run four benchmarks. Note that for all of them we
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run the main function once in advance, to let the JIT recoginizing the hot
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run the main function once in advance, to let the JIT recognize the hot
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loops and emitting the corresponding code. Thus, the results reported do
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<strong>not</strong> include the time spent by the JIT compiler itself, but give a good
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measure of how good is the code generated by the JIT. At this point in time,
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<p>The next step is probably to find an alternative implementation that does not
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use tail calls: this probably will also improve the time spent by the JIT
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compiler itself, which is not reported in the numbers above but that so far it
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is surely too high to be acceptable. Stay tuned.</p></body></html>
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is surely too high to be acceptable. Stay tuned.</p></body></html>

‎posts/2010/03/hello-5058108566628405592.html

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<html><body><p>Hello.</p>
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<p>I recently did some benchmarking of <a class="reference external" href="https://twistedmatrix.com">twisted</a> on top of PyPy. For the very
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impatient: <b>PyPy is up to 285% faster than CPython</b>. For more patient people,
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there is a full explanation of what I did and how I performed measurments,
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there is a full explanation of what I did and how I performed measurements,
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so they can judge themselves.</p>
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<p>The benchmarks are living in <a class="reference external" href="https://code.launchpad.net/~exarkun/+junk/twisted-benchmarks">twisted-benchmarks</a> and were mostly written
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by <a class="reference external" href="https://jcalderone.livejournal.com/">Jean Paul Calderone</a>. Even though he called them "initial exploratory
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average benchmarks found out there.</p>
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<p>The methodology was to run each benchmark for
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quite some time (about 1 minute), measuring number of requests each 5s.
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Then I looked at <a class="reference external" href="https://codespeak.net/svn/user/fijal/txt/twisted-data.txt">dump</a> of data and substracted some time it took
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Then I looked at <a class="reference external" href="https://codespeak.net/svn/user/fijal/txt/twisted-data.txt">dump</a> of data and subtracted some time it took
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for JIT-capable interpreters to warm up (up to 15s), averaging
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everything after that. Averages of requests per second are in the table below (the higher the better):</p>
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<table border="1" class="docutils">
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</ul>
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<p>Twisted version used: svn trunk, revision 28580</p>
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<p>Machine: unfortunately 32bit virtual-machine under qemu, running ubuntu karmic,
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on top of Quad core intel Q9550 with 6M cache. Courtesy of Michael Schneider.</p></body></html>
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on top of Quad core intel Q9550 with 6M cache. Courtesy of Michael Schneider.</p></body></html>

‎posts/2015/02/.linalg-support-in-pypynumpy-comment-3338463064440291817.html

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<html><body><p>What blog post somehow fails to mention is that we do not reimplement those but reuse whatever underlaying library is there. The measurments of the actual speed is then not that interesting, because we're only interested in the overhead of call.</p></body></html>
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<html><body><p>What blog post somehow fails to mention is that we do not reimplement those but reuse whatever underlaying library is there. The measurements of the actual speed is then not that interesting, because we're only interested in the overhead of call.</p></body></html>

‎posts/2015/03/.pypy-251-released-comment-6594177931272237550.html

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<html><body><p>Memory footprint is tricky to measure. PyPy usually starts at 60M (as opposed to say 6 for cpython), but then data structures are smaller. We'll try to get some measurments going on some point. Benchmarking is hard :-)<br><br>No, PyPy3 is not as fast as PyPy2. We should really look into it at some point.</p></body></html>
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<html><body><p>Memory footprint is tricky to measure. PyPy usually starts at 60M (as opposed to say 6 for cpython), but then data structures are smaller. We'll try to get some measurements going on some point. Benchmarking is hard :-)<br><br>No, PyPy3 is not as fast as PyPy2. We should really look into it at some point.</p></body></html>

‎posts/2017/10/how-to-make-your-code-80-times-faster-1424098117108093942.html

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2x faster than the original CPython. At this point, most people would be happy
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and go tweeting how PyPy is great.<br>
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<br>
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In general, when talking of CPython vs PyPy, I am rarely satified of a 2x
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In general, when talking of CPython vs PyPy, I am rarely satisfied with a 2x
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speedup: I know that PyPy can do much better than this, especially if you
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write code which is specifically optimized for the JIT. For a real-life
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example, have a look at <a class="reference external" href="https://capnpy.readthedocs.io/en/latest/benchmarks.html">capnpy benchmarks</a>, in which the PyPy version is
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actual array. Then we have a long list of 149 simple operations which set the
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fields of the resulting array, construct an iterator, and finally do a
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<tt class="docutils literal">call_assembler</tt>: this is the actual logic to do the addition, which was
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JITtted indipendently; <tt class="docutils literal">call_assembler</tt> is one of the operations to do
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JITtted independently; <tt class="docutils literal">call_assembler</tt> is one of the operations to do
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JIT-to-JIT calls:<br>
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<div class="separator" style="clear: both; text-align: center;">
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<a href="https://1.bp.blogspot.com/-vmo0pWharIU/Wfb3VfwHjxI/AAAAAAAABNE/a6Em09qZizwGiWJeTbGzKfHQH70dB7RKgCEwYBhgL/s1600/2017-10-trace2.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="640" src="https://1.bp.blogspot.com/-vmo0pWharIU/Wfb3VfwHjxI/AAAAAAAABNE/a6Em09qZizwGiWJeTbGzKfHQH70dB7RKgCEwYBhgL/s640/2017-10-trace2.png" width="625"></a></div>

‎posts/2021/04/pypy-v734-release-of-python-27-and-37.txt

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In any case both `cibuildwheel`_ and the `multibuild system`_ support
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building wheels for PyPy.
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.. _`PyPy`: https://doc.pypy.org/
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.. _`RPython`: https://rpython.readthedocs.org
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.. _`help`: project-ideas.html
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.. _`help`: https://doc.pypy.org/en/latest/project-ideas.html
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.. _`CFFI`: https://cffi.readthedocs.io
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‎posts/2021/05/pypy-v735-release.rst

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‎posts/2021/10/pypy-v737-release.rst

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‎posts/2022/02/pypyv738-release.txt

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‎posts/2022/03/pypyv739-release.rst

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‎posts/2022/12/pypy-v7310-release.txt

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‎posts/2022/12/pypy-v7311-release.txt

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‎posts/2023/06/pypy-v7312-release.txt

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‎posts/2023/09/pypy-v7313-release.txt

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‎posts/2023/12/pypy-v7314-release.txt

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.. _HPy-0.9: https://hpyproject.org/blog/posts/2023/10/hpy-0.9.0-fourth-public-release/

‎posts/2024/01/pypy-v7315-release.txt

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‎posts/2024/04/pypy-v7316-release.txt

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‎posts/2024/08/pypy-v7317-release.txt

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‎posts/2025/02/pypy-v7318-release.txt

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