[pypy-commit] pypy.org extradoc: Add the complete EP talks
arigo
noreply at buildbot.pypy.org
Wed Aug 20 16:52:42 CEST 2014
Author: Armin Rigo <arigo at tunes.org>
Branch: extradoc
Changeset: r528:f25b6226ae59
Date: 2014-08-20 16:52 +0200
http://bitbucket.org/pypy/pypy.org/changeset/f25b6226ae59/
Log: Add the complete EP talks
diff --git a/talk/ep2014-status.html b/talk/ep2014-status.html
--- a/talk/ep2014-status.html
+++ b/talk/ep2014-status.html
@@ -368,6 +368,9 @@
EuroPython (except last year; hence the "no no, PyPy is not dead" part
of the title of this talk).</p>
</div>
+<hr><center>
+<a href="ep2014-status.pdf"><b>See the complete talk (in pdf)</b></a>
+</center>
</div>
</body>
</html>
diff --git a/talk/ep2014-status.pdf b/talk/ep2014-status.pdf
new file mode 100644
index 0000000000000000000000000000000000000000..aa6078c72592f3c1704408ce9759135c24a70c28
GIT binary patch
[cut]
diff --git a/talk/ep2014-stm.html b/talk/ep2014-stm.html
--- a/talk/ep2014-stm.html
+++ b/talk/ep2014-stm.html
@@ -374,6 +374,9 @@
languages like Python. I will also mention CPython: how hard (or not)
it would be to change the CPython source code to use the same approach.</p>
</div>
+<hr><center>
+<a href="ep2014-stm/talk.html"><b>See the complete talk (in html)</b></a>
+</center>
</div>
</body>
</html>
diff --git a/talk/ep2014-stm/fig4.svg b/talk/ep2014-stm/fig4.svg
new file mode 100644
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diff --git a/talk/ep2014-stm/talk.html b/talk/ep2014-stm/talk.html
new file mode 100644
--- /dev/null
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+
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+<div id="controls"></div>
+<div id="currentSlide"></div>
+<div id="header">
+
+</div>
+<div id="footer">
+<h1>Using All These Cores: Transactional Memory in PyPy</h1>
+
+</div>
+</div>
+<div class="presentation">
+<div class="slide" id="slide0">
+<h1 class="title">Using All These Cores: Transactional Memory in PyPy</h1>
+
+<center><p><strong>Armin Rigo - EuroPython 2014</strong></p>
+</center>
+</div>
+<div class="slide" id="part-1-intro-and-current-status">
+<h1>Part 1 - Intro and Current Status</h1>
+</div>
+<div class="slide" id="introduction">
+<h1>Introduction</h1>
+<ul class="simple">
+<li>PyPy-STM: Software Transactional Memory</li>
+<li>On-going research project:<ul>
+<li>by Remi Meier and myself</li>
+<li>helped by crowdfunding, thanks to all donors</li>
+</ul>
+</li>
+<li>Started as a EuroPython 2011 lightning talk</li>
+</ul>
+</div>
+<div class="slide" id="why-is-there-a-gil">
+<h1>Why is there a GIL?</h1>
+<ul class="simple">
+<li>GIL = Global Interpreter Lock</li>
+<li>initially: CPython was single threaded</li>
+<li>for concurrency (but not parallelism):<ul>
+<li>provide concurrently running threads</li>
+</ul>
+</li>
+<li>easiest way to retrofit into interpreter:<ul>
+<li>acquire GIL around the execution of bytecode instructions</li>
+<li>easy for refcounting, too</li>
+</ul>
+</li>
+</ul>
+</div>
+<div class="slide" id="consequences">
+<h1>Consequences (+)</h1>
+<ul class="simple">
+<li>atomic & isolated instructions:<ul>
+<li>things like <tt class="docutils literal">list.append()</tt> are atomic</li>
+<li>tons of websites mention this</li>
+<li>latent races if Python becomes really parallel</li>
+</ul>
+</li>
+<li>sequential consistency:<ul>
+<li>less surprises; "all variables volatile"</li>
+</ul>
+</li>
+</ul>
+</div>
+<div class="slide" id="id1">
+<h1>Consequences (-)</h1>
+<ul class="simple">
+<li>obviously, no parallelism</li>
+<li>GIL not available to application:<ul>
+<li>all difficulties of concurrency still there</li>
+<li>need application-level locking</li>
+</ul>
+</li>
+</ul>
+</div>
+<div class="slide" id="removing-the-gil">
+<h1>Removing the GIL</h1>
+<ul class="simple">
+<li><ol class="first arabic">
+<li>Fine-grained locking</li>
+</ol>
+</li>
+<li><ol class="first arabic" start="2">
+<li>Shared-nothing</li>
+</ol>
+</li>
+<li><ol class="first arabic" start="3">
+<li>Transactional memory</li>
+</ol>
+</li>
+</ul>
+</div>
+<div class="slide" id="fine-grained-locking">
+<h1>Fine-grained locking</h1>
+<ul class="simple">
+<li>replace GIL with locks on objs / data structures</li>
+<li>accessing different objects can run in parallel</li>
+<li>harder to implement:<ul>
+<li>many locks -> deadlock risks</li>
+<li>refcounting issue</li>
+</ul>
+</li>
+<li>overhead of lock/unlock on objs:<ul>
+<li>Jython depends on JVM for good lock removal</li>
+</ul>
+</li>
+<li>still need application-level locking</li>
+</ul>
+</div>
+<div class="slide" id="shared-nothing">
+<h1>Shared-nothing</h1>
+<ul class="simple">
+<li>each independent part of the program gets its own interpreter</li>
+<li>simple implementation</li>
+<li>gives workaround instead of direct replacement</li>
+<li>not compatible to existing threaded applications, a priori</li>
+<li>explicit communication:<ul>
+<li>good: clean model, no locks</li>
+<li>bad: limitations, overhead</li>
+</ul>
+</li>
+</ul>
+</div>
+<div class="slide" id="transactional-memory">
+<h1>Transactional Memory</h1>
+<ul class="simple">
+<li>like GIL, but instead of blocking, each thread runs optimistically</li>
+<li>"easy" to implement:<ul>
+<li>GIL acquire -> transaction start</li>
+<li>GIL release -> transaction commit</li>
+</ul>
+</li>
+<li>overhead: cross-checking conflicting memory reads and writes,
+and if necessary, cancel and restart transactions</li>
+<li>HTM, STM, or some hybrids exist:<ul>
+<li>but mostly still research-only</li>
+</ul>
+</li>
+</ul>
+</div>
+<div class="slide" id="pypy-stm">
+<h1>PyPy-STM</h1>
+<ul class="simple">
+<li>implementation of a specially-tailored STM ("hard" part):<ul>
+<li>a reusable C library</li>
+<li>called STMGC-C7</li>
+</ul>
+</li>
+<li>used in PyPy to replace the GIL ("easy" part)</li>
+<li>could also be used in CPython<ul>
+<li>but refcounting needs replacing</li>
+</ul>
+</li>
+</ul>
+</div>
+<div class="slide" id="how-does-it-work">
+<h1>How does it work?</h1>
+<object data="fig4.svg" type="image/svg+xml">
+fig4.svg</object>
+</div>
+<div class="slide" id="demo">
+<h1>Demo</h1>
+<ul class="simple">
+<li>counting primes</li>
+</ul>
+</div>
+<div class="slide" id="long-transactions">
+<h1>Long Transactions</h1>
+<ul class="simple">
+<li>threads and application-level locks still needed...</li>
+<li>but <em>can be very coarse:</em><ul>
+<li>two transactions can optimistically run in parallel</li>
+<li>even if they both <em>acquire and release the same lock</em></li>
+</ul>
+</li>
+</ul>
+</div>
+<div class="slide" id="id2">
+<h1>Long Transactions</h1>
+<object data="fig4.svg" type="image/svg+xml">
+fig4.svg</object>
+</div>
+<div class="slide" id="id3">
+<h1>Demo</h1>
+<ul class="simple">
+<li>Bottle web server</li>
+</ul>
+</div>
+<div class="slide" id="pypy-stm-programming-model">
+<h1>PyPy-STM Programming Model</h1>
+<ul class="simple">
+<li>threads-and-locks, fully compatible with the GIL</li>
+<li>this is not "everybody should use careful explicit threading
+with all the locking issues"</li>
+<li>instead, PyPy-STM pushes forward:<ul>
+<li>make or use a thread pool library</li>
+<li>coarse locking, inside that library only</li>
+</ul>
+</li>
+</ul>
+</div>
+<div class="slide" id="id4">
+<h1>PyPy-STM Programming Model</h1>
+<ul class="simple">
+<li>e.g.:<ul>
+<li><tt class="docutils literal">multiprocessing</tt>-like thread pool</li>
+<li>Twisted/Tornado/Bottle extension</li>
+<li>Stackless/greenlet/gevent extension</li>
+</ul>
+</li>
+</ul>
+</div>
+<div class="slide" id="pypy-stm-status">
+<h1>PyPy-STM status</h1>
+<ul class="simple">
+<li>current status:<ul>
+<li>basics work</li>
+<li>best case 25-40% overhead (much better than originally planned)</li>
+<li>app locks not done yet ("with atomic" workaround)</li>
+<li>tons of things to improve</li>
+<li>tons of things to improve</li>
+<li>tons of things to improve</li>
+<li>tons of things to improve</li>
+<li>tons of things to improve</li>
+<li>tons of things to improve</li>
+<li>tons of things to improve</li>
+</ul>
+</li>
+</ul>
+</div>
+<div class="slide" id="summary-benefits">
+<h1>Summary: Benefits</h1>
+<ul class="simple">
+<li>Potential to enable parallelism:<ul>
+<li>in any CPU-bound multithreaded program</li>
+<li>or as a replacement of <tt class="docutils literal">multiprocessing</tt></li>
+<li>but also in existing applications not written for that</li>
+<li>as long as they do multiple things that are "often independent"</li>
+</ul>
+</li>
+<li>Keep locks coarse-grained</li>
+</ul>
+</div>
+<div class="slide" id="summary-issues">
+<h1>Summary: Issues</h1>
+<ul class="simple">
+<li>Keep locks coarse-grained:<ul>
+<li>but in case of systematic conflicts, performance is bad again</li>
+<li>need to track and fix them</li>
+<li>need tool to support this (debugger/profiler)</li>
+</ul>
+</li>
+<li>Performance hit: 25-40% slower than a plain PyPy-JIT (may be ok)</li>
+</ul>
+</div>
+<div class="slide" id="summary-pypy-stm">
+<h1>Summary: PyPy-STM</h1>
+<ul class="simple">
+<li>Not production-ready</li>
+<li>But it has the potential to enable "easier parallelism for everybody"</li>
+<li>Still alpha but slowly getting there!<ul>
+<li>see <a class="reference external" href="http://morepypy.blogspot.com/">http://morepypy.blogspot.com/</a></li>
+</ul>
+</li>
+<li>Crowdfunding!<ul>
+<li>see <a class="reference external" href="http://pypy.org/">http://pypy.org/</a></li>
+</ul>
+</li>
+</ul>
+</div>
+<div class="slide" id="part-2-under-the-hood">
+<h1>Part 2 - Under The Hood</h1>
+<p><strong>STMGC-C7</strong></p>
+</div>
+<div class="slide" id="overview">
+<h1>Overview</h1>
+<ul class="simple">
+<li>Say we want to run N = 2 threads</li>
+<li>We reserve twice the memory</li>
+<li>Thread 1 reads/writes "memory segment" 1</li>
+<li>Thread 2 reads/writes "memory segment" 2</li>
+<li>Upon commit, we (try to) copy the changes to the other segment</li>
+</ul>
+</div>
+<div class="slide" id="trick-1">
+<h1>Trick #1</h1>
+<ul class="simple">
+<li>Objects contain pointers to each other</li>
+<li>These pointers are relative instead of absolute:<ul>
+<li>accessed as if they were "thread-local data"</li>
+<li>the x86 has a zero-cost way to do that (<tt class="docutils literal">%fs</tt>, <tt class="docutils literal">%gs</tt>)</li>
+<li>supported in clang (not gcc so far)</li>
+</ul>
+</li>
+</ul>
+</div>
+<div class="slide" id="trick-2">
+<h1>Trick #2</h1>
+<ul class="simple">
+<li>With Trick #1, most objects are exactly identical in all N segments:<ul>
+<li>so we share the memory</li>
+<li><tt class="docutils literal">mmap() MAP_SHARED</tt></li>
+<li>actual memory usage is multiplied by much less than N</li>
+</ul>
+</li>
+<li>Newly allocated objects are directly in shared pages:<ul>
+<li>we don't actually need to copy <em>all new objects</em> at commit,
+but only the few <em>old objects</em> modified</li>
+</ul>
+</li>
+</ul>
+</div>
+<div class="slide" id="barriers">
+<h1>Barriers</h1>
+<ul class="simple">
+<li>Need to record all reads and writes done by a transaction</li>
+<li>Extremely cheap way to do that:<ul>
+<li><em>Read:</em> set a flag in thread-local memory (one byte)</li>
+<li><em>Write</em> into a newly allocated object: nothing to do</li>
+<li><em>Write</em> into an old object: add the object to a list</li>
+</ul>
+</li>
+<li>Commit: check if each object from that list conflicts with
+a read flag set in some other thread</li>
+</ul>
+</div>
+<div class="slide" id="id5">
+<h1>...</h1>
+</div>
+<div class="slide" id="thank-you">
+<h1>Thank You</h1>
+<ul class="simple">
+<li><a class="reference external" href="http://morepypy.blogspot.com/">http://morepypy.blogspot.com/</a></li>
+<li><a class="reference external" href="http://pypy.org/">http://pypy.org/</a></li>
+<li>irc: <tt class="docutils literal">#pypy</tt> on freenode.net</li>
+</ul>
+</div>
+</div>
+</body>
+</html>
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+../stanford-ee380-2011/ui
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