[pypy-commit] pypy.org extradoc: numpy donation campaign

fijal noreply at buildbot.pypy.org
Wed Oct 12 22:39:07 CEST 2011 

Author: Maciej Fijalkowski <fijall at gmail.com>
Branch: extradoc
Changeset: r280:e9995d9c9546
Date: 2011-10-12 22:38 +0200
http://bitbucket.org/pypy/pypy.org/changeset/e9995d9c9546/

Log:	numpy donation campaign

diff --git a/numpydonate.html b/numpydonate.html
new file mode 100644
--- /dev/null
+++ b/numpydonate.html
@@ -0,0 +1,201 @@
+<!DOCTYPE html>
+<html>
+<head>
+	<title>PyPy :: Call for donations - PyPy to support Numpy!</title>
+	<meta http-equiv="content-language" content="en" />
+	<meta http-equiv="content-type" content="text/html; charset=utf-8" />
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+	<hr class="clear" />
+</div>
+<div id="content">
+<div>
+<div id="main">
+<h1 class="title">Call for donations - PyPy to support Numpy!</h1>
+<div class="section" id="make-numpy-for-pypy-happen">
+<h1>Make NumPy for PyPy happen</h1>
+<p>This is a proposal to provide a fully compatible working <a class="reference external" href="http://numpy.scipy.org/">NumPy</a> implementation
+for PyPy. This has long been a very commonly <a class="reference external" href="http://morepypy.blogspot.com/2011/06/report-back-from-our-survey.html">requested feature</a> for PyPy
+as well as a worthy goal given that PyPy performs extremely well on numeric
+workloads.</p>
+<p>We already had some success providing a very basic NumPy implementation,
+however we believe that raising funds can significantly speed up its
+development, by paying people to work full time on it.</p>
+<p>Below you'll find the <a class="reference internal" href="#work-plan">work plan</a> and the associated
+fundraising targets we need to make things happen.  Once we reach the
+necessary target for each stage, we will start contracting
+developers.  Contracts and money are managed by the non-profit
+<a class="reference external" href="http://sfconservancy.org/">Software Freedom Conservancy</a> of which the PyPy project is a member.
+The current elected representatives are Carl Friedrich Bolz, Holger
+Krekel and Jacob Hallen and they will &#8211; in close collaboration with
+Conservancy and the core developers &#8211; select the best developers for
+implementing NumPy among well known PyPy contributors.</p>
+<p>Should we not receive enough donations to complete all stages by 1st March 2012
+at the latest, we will try our best to make PyPy support NumPy anyway.  We
+however reserve the right to shift any unused funds to other PyPy activities
+when that date is reached.  Of course, since the Conservancy is a
+501(c)(3) charitable organization incorporated in NY, USA, all funds will,
+regardless of their use, be spent in a way that benefits the general
+public, the advancement of Open Source and Free Software,
+and in particular the PyPy community and the PyPy codebase.</p>
+<p><strong>Note</strong> For donations higher than $1,000, we can arrange for an invoice
+and a different payment method to avoid the high Paypal fees.  Please
+contact pypy at sfconservancy.org if you want to know details on how
+to donate via other means.</p>
+<div class="section" id="what-is-numpy">
+<h2>What is NumPy?</h2>
+<p><a class="reference external" href="http://numpy.scipy.org/">NumPy</a> is a framework for doing numerical calculations in Python. It has
+become the de-facto standard for doing any kinds of computations that involve
+n-dimensional arrays. Please consult the NumPy website for more details.</p>
+</div>
+<div class="section" id="why-does-numpy-on-pypy-makes-sense">
+<h2>Why does NumPy on PyPy makes sense?</h2>
+<p>NumPy on PyPy makes sense for a couple of reasons: Firstly, it is by
+far the most requested feature from PyPy. Secondly, PyPy <a class="reference external" href="http://morepypy.blogspot.com/2011/07/realtime-image-processing-in-python.html">performs
+well</a> on numerical loads already.  Therefore bringing NumPy into the
+equation is a reasonable next step - as it's a very convenient and popular tool
+for doing this kind of work. The resulting implementation should move
+Python in scientific world from being a merely &ldquo;glue&rdquo; language into
+being the main implementation language for a lot of people in
+the scientific/numeric worlds. This will benefit current users of NumPy as
+well as people who so far have to cope with lower level languages like C
+or Fortran for speed purposes.</p>
+</div>
+<div class="section" id="speed">
+<h2>Speed</h2>
+<p>The current implementation of NumPy on PyPy is reasonably fast - it ranges
+from roughly the same speed to 2-5x faster for stacked large array operations
+to 100-300x for accessing NumPy array elements one by one. The exact speed
+depends very much how NumPy is used, but the target would be to be within an
+order of magnitude from handwritten C.
+To achieve this, we would
+need to teach our JIT backends how to use modern vector instructions, like SSE
+or AVM. Hence, we split the proposal into two parts, first part covers compatibility
+with a reasonable approach to keeping current speed achievements, second part
+is about teaching the JIT how to vectorize certain operations, which should bring
+PyPy's NumPy as a very competitive tool compared to other available
+solutions for numerical computations, like matlab or C++ array libraries.</p>
+</div>
+</div>
+<div class="section" id="id1">
+<span id="work-plan"></span><h1>Work plan</h1>
+<div class="section" id="about-estimates-and-costs">
+<h2>About estimates and costs</h2>
+<p>For each step, we estimated the time that it would take to complete for an
+experienced developer who is already familiar with the PyPy codebase.  From
+this number, the money is calculated considering a hourly rate of $60, and a
+5% general donation which goes to the <a class="reference external" href="http://sfconservancy.org/">Software Freedom Conservancy</a> itself, the non-profit
+organization of which the PyPy project is a member and which manages all the
+issues related to donations, payments, and tax-exempt status.</p>
+<p>We split the proposal into two parts - we plan to implement them in the same
+order, starting by the time we raise the corresponding funding targets:</p>
+<ul>
+<li><p class="first"><strong>Compatibility</strong>:</p>
+<p>This part covers the core NumPy Python API. We'll implement all NumPy APIs
+that are officially documented and we'll pass all of NumPy's tests that
+cover documented APIs and are not implementation details.
+Specifically, we don't plan to:</p>
+<ul class="simple">
+<li>implement NumPy's C API</li>
+<li>implement other scientific libraries, like SciPy, matplotlib or biopython</li>
+</ul>
+<p>Estimated costs: USD$30,000. Estimated duration: 3 months.</p>
+</li>
+<li><p class="first"><strong>Speed</strong>:</p>
+<p>This part will cover significant speed improvements in the JIT that would
+make numeric computations faster. This includes, but is not necesarilly
+limited to:</p>
+<ul class="simple">
+<li>write a set of benchmarks covering various use cases</li>
+<li>teaching the JIT backend (or multiple backends) how to deal with vector
+operations, like SSE</li>
+<li>experiments with automatic parallelization using multiple threads, akin
+to numexpr</li>
+<li>improving the JIT register allocator that will make a difference, especially
+for tight loops</li>
+</ul>
+<p>As with all speed improvements, it's relatively hard to predict exactly
+how it'll cope, however we expect the results to be in the range of
+XXX I (cfbolz) find this claim too strong
+handwritten C equivalent, sometimes outperforming it in cases where static
+compilation of C prevents some advanced optimization techniques.</p>
+<p>Estimated costs: USD$30,000. Estimated duration: 3 months.</p>
+</li>
+</ul>
+</div>
+</div>
+<div class="section" id="benefits-of-this-work-to-the-python-community-and-the-general-public">
+<h1>Benefits of This Work to the Python Community and the General Public</h1>
+<p>Python has become one of the most popular dynamic programming languages in
+the world.  Web developers, educators, and scientific programmers alike
+all value Python because Python code is often more readable and because
+Python often increases programmer productivity.</p>
+<p>Traditionally, languages like Python ran more slowly than static, compiled
+languages; Python developers chose to sacrifice execution speed for ease
+of programming.  The PyPy project created a substantially improved Python
+language implementation, including a fast Just-in-time (JIT) compiler.
+The increased execution speed that PyPy provides has attracted many users,
+who now find their Python code runs up to four times faster under PyPy
+than under the reference implementation written in C.</p>
+<p>Meanwhile, adoption of Python is already underway for those researchers
+and developers who work specifically on computing that requires fast
+numeric operations.  Numpy support in PyPy will allow for Python's use by
+those developers and researchers who want the ease of programming that
+Python provides, the speed of PyPy, <em>and</em> the speedups for numerical work
+that Numpy can provide.</p>
+<p>PyPy's developers make all PyPy software available to the public without
+charge, under PyPy's Open Source copyright license, the permissive MIT
+License.  PyPy's license assures that PyPy is equally available to
+everyone freely on terms that allow both non-commercial and commercial
+activity.  This license allows for academics, for-profit software
+developers, volunteers and enthusiasts alike to collaborate together to
+make a better Python implementation for everyone.</p>
+<p>NumPy support for PyPy will be licensed similarly, and therefore NumPy
+support can directly help researchers and developers who seek to do
+numeric computing but want an easier programming language to use than
+Fortan or C, which is typically used for these applications.  Being
+licensed freely to the general public means that opportunities to use,
+improve and learn about how NumPy works itself will be generally available
+to everyone.</p>
+</div>
+</div>
+<div id="sidebar">
+</div>
+</div>
+</div>
+</div></div></div>
+</body>
+</html>
\ No newline at end of file
diff --git a/source/numpydonate.txt b/source/numpydonate.txt
new file mode 100644
--- /dev/null
+++ b/source/numpydonate.txt
@@ -0,0 +1,181 @@
+---
+layout: page
+title: Call for donations - PyPy to support Numpy!
+---
+
+Make NumPy for PyPy happen
+==========================
+
+This is a proposal to provide a fully compatible working `NumPy`_ implementation
+for PyPy. This has long been a very commonly `requested feature`_ for PyPy
+as well as a worthy goal given that PyPy performs extremely well on numeric
+workloads.
+
+We already had some success providing a very basic NumPy implementation,
+however we believe that raising funds can significantly speed up its
+development, by paying people to work full time on it.
+
+Below you'll find the `work plan`_ and the associated
+fundraising targets we need to make things happen.  Once we reach the
+necessary target for each stage, we will start contracting
+developers.  Contracts and money are managed by the non-profit
+`Software Freedom Conservancy`_ of which the PyPy project is a member.
+The current elected representatives are Carl Friedrich Bolz, Holger
+Krekel and Jacob Hallen and they will &#8211; in close collaboration with
+Conservancy and the core developers &#8211; select the best developers for
+implementing NumPy among well known PyPy contributors.
+
+Should we not receive enough donations to complete all stages by 1st March 2012
+at the latest, we will try our best to make PyPy support NumPy anyway.  We
+however reserve the right to shift any unused funds to other PyPy activities
+when that date is reached.  Of course, since the Conservancy is a
+501(c)(3) charitable organization incorporated in NY, USA, all funds will,
+regardless of their use, be spent in a way that benefits the general
+public, the advancement of Open Source and Free Software,
+and in particular the PyPy community and the PyPy codebase. 
+
+**Note** For donations higher than $1,000, we can arrange for an invoice
+and a different payment method to avoid the high Paypal fees.  Please
+contact pypy at sfconservancy.org if you want to know details on how
+to donate via other means.
+
+.. _`Software Freedom Conservancy`: http://sfconservancy.org/
+
+What is NumPy?
+--------------
+
+`NumPy`_ is a framework for doing numerical calculations in Python. It has
+become the de-facto standard for doing any kinds of computations that involve
+n-dimensional arrays. Please consult the NumPy website for more details.
+
+Why does NumPy on PyPy makes sense?
+-----------------------------------
+
+NumPy on PyPy makes sense for a couple of reasons: Firstly, it is by
+far the most requested feature from PyPy. Secondly, PyPy `performs
+well`_ on numerical loads already.  Therefore bringing NumPy into the
+equation is a reasonable next step - as it's a very convenient and popular tool
+for doing this kind of work. The resulting implementation should move
+Python in scientific world from being a merely "glue" language into
+being the main implementation language for a lot of people in
+the scientific/numeric worlds. This will benefit current users of NumPy as
+well as people who so far have to cope with lower level languages like C
+or Fortran for speed purposes.
+
+.. _`NumPy`: http://numpy.scipy.org/
+.. _`requested feature`: http://morepypy.blogspot.com/2011/06/report-back-from-our-survey.html
+.. _`NumPy imlpementation`: http://morepypy.blogspot.com/2011/05/numpy-in-pypy-status-and-roadmap.html
+.. _`performs well`: http://morepypy.blogspot.com/2011/07/realtime-image-processing-in-python.html
+
+Speed
+-----
+
+The current implementation of NumPy on PyPy is reasonably fast - it ranges
+from roughly the same speed to 2-5x faster for stacked large array operations
+to 100-300x for accessing NumPy array elements one by one. The exact speed
+depends very much how NumPy is used, but the target would be to be within an
+order of magnitude from handwritten C.
+To achieve this, we would
+need to teach our JIT backends how to use modern vector instructions, like SSE
+or AVM. Hence, we split the proposal into two parts, first part covers compatibility
+with a reasonable approach to keeping current speed achievements, second part
+is about teaching the JIT how to vectorize certain operations, which should bring
+PyPy's NumPy as a very competitive tool compared to other available
+solutions for numerical computations, like matlab or C++ array libraries.
+
+.. _`work plan`:
+
+Work plan
+=========
+
+About estimates and costs
+-------------------------
+
+For each step, we estimated the time that it would take to complete for an
+experienced developer who is already familiar with the PyPy codebase.  From
+this number, the money is calculated considering a hourly rate of $60, and a
+5% general donation which goes to the `Software Freedom Conservancy`_ itself, the non-profit
+organization of which the PyPy project is a member and which manages all the
+issues related to donations, payments, and tax-exempt status.
+
+.. _`Software Freedom Conservancy`: http://sfconservancy.org/
+
+We split the proposal into two parts - we plan to implement them in the same
+order, starting by the time we raise the corresponding funding targets:
+
+* **Compatibility**:
+
+  This part covers the core NumPy Python API. We'll implement all NumPy APIs
+  that are officially documented and we'll pass all of NumPy's tests that
+  cover documented APIs and are not implementation details.
+  Specifically, we don't plan to:
+
+  * implement NumPy's C API
+
+  * implement other scientific libraries, like SciPy, matplotlib or biopython
+
+  Estimated costs: USD$30,000. Estimated duration: 3 months.
+
+* **Speed**:
+
+  This part will cover significant speed improvements in the JIT that would
+  make numeric computations faster. This includes, but is not necesarilly
+  limited to:
+
+  * write a set of benchmarks covering various use cases
+
+  * teaching the JIT backend (or multiple backends) how to deal with vector
+    operations, like SSE
+
+  * experiments with automatic parallelization using multiple threads, akin
+    to numexpr
+
+  * improving the JIT register allocator that will make a difference, especially
+    for tight loops
+
+  As with all speed improvements, it's relatively hard to predict exactly
+  how it'll cope, however we expect the results to be in the range of
+  XXX I (cfbolz) find this claim too strong
+  handwritten C equivalent, sometimes outperforming it in cases where static
+  compilation of C prevents some advanced optimization techniques.
+
+  Estimated costs: USD$30,000. Estimated duration: 3 months.
+
+Benefits of This Work to the Python Community and the General Public
+====================================================================
+
+Python has become one of the most popular dynamic programming languages in
+the world.  Web developers, educators, and scientific programmers alike
+all value Python because Python code is often more readable and because
+Python often increases programmer productivity.
+
+Traditionally, languages like Python ran more slowly than static, compiled
+languages; Python developers chose to sacrifice execution speed for ease
+of programming.  The PyPy project created a substantially improved Python
+language implementation, including a fast Just-in-time (JIT) compiler.
+The increased execution speed that PyPy provides has attracted many users,
+who now find their Python code runs up to four times faster under PyPy
+than under the reference implementation written in C.
+
+Meanwhile, adoption of Python is already underway for those researchers
+and developers who work specifically on computing that requires fast
+numeric operations.  Numpy support in PyPy will allow for Python's use by
+those developers and researchers who want the ease of programming that
+Python provides, the speed of PyPy, *and* the speedups for numerical work
+that Numpy can provide.
+
+PyPy's developers make all PyPy software available to the public without
+charge, under PyPy's Open Source copyright license, the permissive MIT
+License.  PyPy's license assures that PyPy is equally available to
+everyone freely on terms that allow both non-commercial and commercial
+activity.  This license allows for academics, for-profit software
+developers, volunteers and enthusiasts alike to collaborate together to
+make a better Python implementation for everyone.
+
+NumPy support for PyPy will be licensed similarly, and therefore NumPy
+support can directly help researchers and developers who seek to do
+numeric computing but want an easier programming language to use than
+Fortan or C, which is typically used for these applications.  Being
+licensed freely to the general public means that opportunities to use,
+improve and learn about how NumPy works itself will be generally available
+to everyone.

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