Author: Richard Plangger <planri...@gmail.com>
Branch: extradoc
Changeset: r5734:4fc29c6d0bc8
Date: 2016-10-06 14:00 +0200
http://bitbucket.org/pypy/extradoc/changeset/4fc29c6d0bc8/
Log: some more changes for my talk
diff --git a/talk/pyconza2016/pypy/img/how-jit.png
b/talk/pyconza2016/pypy/img/how-jit.png
new file mode 100644
index
e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..ad9ce720343f9b461e202faacd566abc3a331b61
GIT binary patch
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diff --git a/talk/pyconza2016/pypy/index.html b/talk/pyconza2016/pypy/index.html
--- a/talk/pyconza2016/pypy/index.html
+++ b/talk/pyconza2016/pypy/index.html
@@ -32,16 +32,27 @@
</section>
<section>
<section>
- <h1>PyPy is ..</h1>
+ <h1>More "general" PyPy talk</h1>
+ <p>Goals:</p>
+ <ul>
+ <li>An approach to optimize Python programs</li>
+ <li>Examples</li>
+ <li>How not to start optimizing</li>
+ <li>What is PyPy up to now?</li>
+ </ul>
</section>
+ </section>
+ <section>
<section>
- <p>... a software project ... </p>
+ <h1>PyPy is a ...</h1>
+ <p class="fragment">... <strong>fast virtual machine
for Python</strong> </p>
+ <p class="fragment">developed by researchers,
freelancers and many contributors.</p>
</section>
+ </section>
+ <section>
<section>
- <p>... assembling a <strong>fast virtual machine for
Python</strong> ... </p>
- </section>
- <section>
- <p>developed by many researchers, freelancers and many
contributors.</p>
+ <p><code>$ python yourprogram.py</code></p>
+ <p><code>$ pypy yourprogram.py</code></p>
</section>
</section>
<section>
@@ -66,7 +77,7 @@
<section>
<h1>About me</h1>
<p>Working on PyPy (+1,5y)</p>
- <p>Master degree - Sticked with PyPy</p>
+ <p>Master thesis → GSoC 2015 → PyPy</p>
<p>living and working in Austria</p>
</section>
</section>
@@ -85,17 +96,18 @@
<p><strong>Neither</strong></p>
</section>
<section>
- <p>Run you program an measure your criteria</p>
+ <p>Run your program an measure your
<strong>criteria</strong></p>
</section>
<section>
- <h1>Criteria examples?</h1>
+ <h1>For example?</h1>
<ul>
<li>CPU time</li>
<li>Peak Heap Memory</li>
<li>Requests per second</li>
+ <li>Latency</li>
<li>...</li>
</ul>
- <p>Dissatisfaction with one attribute of your
program!</p>
+ <p>Dissatisfaction with one criteria of your
program!</p>
</section>
</section>
<section>
@@ -103,22 +115,23 @@
<h1>Some theory ... </h1>
</section>
<section>
- <h1>Hot spots</h1>
- <p>Loops!</p>
- <p>What kind program can you build without
loops?</p>
- </section>
- <section>
<h1>Complexity</h1>
- <p>Big-O-Notation - Express how many steps a
program to complete at most</p>
+ <p>Big-O-Notation</p>
+ <p>Classify e.g. a function and it's processing
time</p>
+ <p>Increase input size to the function</p>
</section>
<section>
<ul>
- <li><code>a = 3</code> # runs in
O(1)</li>
- <li><code>[x+1 for x in
range(n)]</code> # runs in O(n)</li>
- <li><code>[[x+y for x in range(n)] for
y in range(m)]</code> # O(n*m)</li>
+ <li><code>a = 3</code> # O(1)</li>
+ <li><code>[x+1 for x in
range(n)]</code> # O(n)</li>
+ <li><code>[[x+y for x in range(n)] \
<br> for y in range(m)]</code> # O(n*m) == O(n) if n > m</li>
</ul>
</section>
<section>
+ Bubble sort vs Quick Sort
+ <p>O(n**2) vs O(n log n)</p>
+ </section>
+ <section>
<h1>Complexity</h1>
<p>Yields the most gain, independent from the
language</p>
<p>E.g. prefer O(n) over O(n**2)</p>
@@ -144,28 +157,43 @@
<li>Written in Python</li>
<li>Moved to vmprof.com</li>
<li>Log files can easily take up to
40MB uncompressed</li>
- <li>Takes ~14 seconds to parse with
CPython</li>
+ <li>Takes ~10 seconds to parse with
CPython</li>
<li>Complexity is linear to input size
of the log file</li>
</ul>
</section>
<section>
+ <p><h3>Thanks to Python</h3></p>
<p class="advantage">+ Little development
time</p>
<p class="advantage">+ Easy to test</p>
- <p><h3>Thanks to Python</h3></p>
</section>
<section>
<p class="disadvantage">- Takes too long to
parse</p>
- <p>Our criteria: CPU time to long</p>
+ <p class="disadvantage">- Parsing is done each
request</p>
+ <p>Our criteria: CPU time to long + requests
per second</p>
+ <p>(Many objects are allocated)</p>
</section>
<section>
- <p class="">Several possible ways</p>
+ <h1>Suggestion</h1>
<p>Caching</p>
<p>Reduce CPU time</p>
<p>Let's have both</p>
</section>
<section>
- <p>Caching - Easily done with django caching
frame work</p>
- <p>Reduce CPU time - Look at vmprof</p>
+ <p>Caching - Easily done with your favourite
caching framework</p>
+ <p>Reduce CPU time - PyPy seems to be good at
that?</p>
+ </section>
+ <section>
+ <h1>Let's run it...</h1>
+ <p><code>$ cpython2.7 parse.py 40mb.log<br>~ 10
seconds</code></p>
+ <p><code>$ pypy2 parse.py 40mb.log<br>~ 2
seconds</code></p>
+ </section>
+ <section>
+ <h1>Caching</h1>
+ <p>Requests really feel instant after the log
has been loaded once</p>
+ <p>Precache</p>
+ </section>
+ <section>
+ <h1>The lazy approach of optimizing Python</h1>
</section>
<section>
<h1>VMProf</h1>
@@ -177,14 +205,16 @@
</section>
<section data-background="img/vmprof-screen-pypy.png">
</section>
- <section>
- <h1>~4 times faster on PyPy</h1>
- </section>
</section>
<section>
<section>
<h1>Introducing PyPy's JIT</h1>
</section>
+ <section>
+ <h1>Hot spots</h1>
+ <p>Loops / Repeat construct!</p>
+ <p>What kind program can you build without
loops?</p>
+ </section>
<section>
<h1>A simplified view</h1>
<ol>
@@ -193,12 +223,17 @@
<li>Optimization stage</li>
<li>Machine code generation</li>
</ol>
- <p>Cannot represent control flow as a graph
(other than loop jumps)</p>
- <p>Guards ensure correctness</p>
+
</section>
<section>
<h1>Beyond the scope of loops</h1>
- <p>Frequent guard failure trigger recording</p>
+ <p>Guards ensure correctness</p>
+ <p>Frequent guard failure triggers recording</p>
+ </section>
+ <section>
+ <h1>Perception</h1>
+ <img src="img/how-jit.png">
+
<small>http://abstrusegoose.com/secretarchives/under-the-hood - CC BY-NC 3.0
US</small>
</section>
<section data-background-image="img/jitlog.png">
<a
href="http://vmprof.com/#/7930e1f54f9eee75084738aafa6cb612/traces";>→
link</a>
@@ -209,6 +244,17 @@
<p>Helps you to learn and understand PyPy</p>
<p>Provided at vmprof.com</p>
</section>
+ <section>
+ <h1>Properties & Tricks</h1>
+ <ul>
+ <li>Type specialization</li>
+ <li>Object unboxing</li>
+ <li>GC scheme</li>
+ <li>Dicts</li>
+ <li>Dynamic class creation (Instance
maps)</li>
+ <li>Function calls (+ Inlining)</li>
+ </ul>
+ </section>
</section>
<section>
<section>
@@ -218,11 +264,11 @@
</section>
<section>
<h1>Magnetic</h1>
- <p>marketing tech company</p>
- <p>switched to PyPy 3 years ago</p>
+ <p>Marketing tech company</p>
+ <p>Switched to PyPy 3 years ago</p>
</section>
<section>
- <h1>Q: what does your service do?</h1>
+ <h1>Q: What does your service do?</h1>
<p>A: ... allow generally large companies to
send targeted marketing (e.g. serve ads) to people based on data we have
learned </p>
</section>
<section>
@@ -242,9 +288,36 @@
<p>So it spends lots of time blocking</p>
</section>
</section>
+ <section>
+ <section>
+ <h1>timeit</h1>
+ <p>why not use perf?</p>
+ <p class="fragment">Try timeit on PyPy</p>
+ </section>
+ <section>
+ <h1>Python 3.5</h1>
+ <p>Progressed quite a bit</p>
+ <p class="fragment">async io</p>
+ <p class="fragment">Many more small details
(sprint?)</p>
+ </section>
+ <section>
+ <h1>C-Extentions</h1>
+ <p>NumPy on top of the emulated layer</p>
+ <p>Boils down to managing PyPy & CPython
objects</p>
+ </section>
+ </section>
+ <section>
+ <section>
+ <h1>Closing example</h1>
+ <p>how to move from cpu limited to network
limited</p>
+ <a
href="https://www.reddit.com/r/Python/comments/kt8bx/ask_rpython_whats_your_experience_with_pypy_and/";>link</a>
+ </section>
+
+ </section>
<section>
<h4>Questions?</h4>
<a
href="morepypy.blogspot.com">morepypy.blogspot.com</a><br>
+ <a href="">software@vimloc.systems</a><br>
Join on IRC <a href="">#pypy</a>
</section>
</div>
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