src/third_party/llvm-project/polly/www/projects.html - cobalt - Git at Google

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   <h1>Open Projects</h1>
   <!--*********************************************************************-->

   LLVM Polly keeps here a list of open projects which each of themselves would
   be a great contribution to Polly. All of these projects are meant to be self
   contained and should take a newcomer around 3-4 months of work. The projects
   we propose are all suiteable as <a
   href="https://developers.google.com/open-source/gsoc/">Google Summer of
   Code</a> projects. In case you are interested in a Google Summer of code
   project make sure to reach out via the Polly <a
   href="http://groups.google.com/group/polly-dev">mailing list</a> early to
   discuss your project proposal.

   <h3>Integrate Polly with the LLVM vectorizers</h3>
   Polly is not only a self-contained optimizer, but also provides a powerful
   dependence and other program analyses. Currently, these analyses are only used
   for our own optimizations. However, LLVM passes such as the loop vectorizer
   would clearly benefit from having direct access to the available Polly
   analyses. In this project, you would define in collaboration with the LLVM
   community and considering existing dependence analysis interface a new
   dependence analysis interface for Polly that allows passes to directly query
   Polly analysis. Even though this project sounds straightforward at a first
   glance, sorting out how to actually make this happen with the current and
   the new pass managers, understanding how and when to invalidate the Polly
   analysis and if dependence information can be computed on-demand make this
   still a challenging project. If successful, this project may be a great way
   to bring features of Polly to standard -O3 optimizations.

   <h3>Register tiling to obtain fast BLAS kernels with Polly</h3>
   Even though Polly is already able to speep up compute kernels significantly,
   when comparing to the best BLAS routines we still are at least one order of
   magnitude off. In this project you will investigate what is needed to close
   this performance gap. Earlier investigations have shown that register tiling
   is one important piece towards this goal. In combination with good tile size
   models and some back-end work, this project is shooting to make common blas
   operations, but also many non-blas kernels competitive with vendor math
   libraries and outperforming the code icc/gcc currently generate.

   <h3>Polly support for Julia - First steps</h3>
   <a href="http://julialang.org/">Julia</a> is a new matlab style programming
   language that provides C like performance for scientific computing. Even
   though Julia also translates to LLVM-IR, parsing and optimizing Julia code
   poses new challenges that currently prevent Polly from optimizing Julia
   code despite the clear need for optimizations such as loop-tiling for Julia.
   In this project you will -- starting from first proof-of-concept patches --
   integrate Polly into Julia and ensure that Julia code can benefit from the
   same high-level loop optimizations as todays C code already does. If time
   permits, making Polly's recent bound-check elimination logic work in Julia
   code would allow the optimization of Julia code, even if save out-of-bound
   checking is used.
   <h3>Interactive Polyhedral Web Calculator</h3>
   At the core of Polly we use the isl math library. isl allows us to describe
   loop transformations with relatively simple higher level operations while
   still providing the full expressiveness of integer polyhedra. To understand
   and describe the transformations we are performing it is often very convenient
   to quickly script example transformations in a scripting language like python.
   isl already comes with a python binding generator, with
   pypyjs there is a python interpreter for the web and with emscriptem isl
   itself can also be compiled to javascript. In this project you combine all
   these components to obtain an interactive polyhedral web calculator, that uses
   latest web technology to nicely illustrate the integer polyhedra you obtain.
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	<html>
	<head>
	<META http-equiv="Content-Type" content="text/html; charset=ISO-8859-1">
	<title>Polly - Polyhedral optimizations for LLVM</title>
	<link type="text/css" rel="stylesheet" href="menu.css">
	<link type="text/css" rel="stylesheet" href="content.css">
	<script src="video-js/video.js" type="text/javascript" charset="utf-8"></script>
	<script type="text/javascript">
	VideoJS.setupAllWhenReady();
	</script>

	<!-- Include the VideoJS Stylesheet -->
	<link rel="stylesheet" href="video-js/video-js.css" type="text/css" media="screen" title="Video JS">
	</head>
	<body>
	<div id="box">
	<!--#include virtual="menu.html.incl"-->
	<div id="content">
	<!--*********************************************************************-->
	<h1>Open Projects</h1>
	<!--*********************************************************************-->

	LLVM Polly keeps here a list of open projects which each of themselves would
	be a great contribution to Polly. All of these projects are meant to be self
	contained and should take a newcomer around 3-4 months of work. The projects
	we propose are all suiteable as <a
	href="https://developers.google.com/open-source/gsoc/">Google Summer of
	Code</a> projects. In case you are interested in a Google Summer of code
	project make sure to reach out via the Polly <a
	href="http://groups.google.com/group/polly-dev">mailing list</a> early to
	discuss your project proposal.

	<h3>Integrate Polly with the LLVM vectorizers</h3>
	Polly is not only a self-contained optimizer, but also provides a powerful
	dependence and other program analyses. Currently, these analyses are only used
	for our own optimizations. However, LLVM passes such as the loop vectorizer
	would clearly benefit from having direct access to the available Polly
	analyses. In this project, you would define in collaboration with the LLVM
	community and considering existing dependence analysis interface a new
	dependence analysis interface for Polly that allows passes to directly query
	Polly analysis. Even though this project sounds straightforward at a first
	glance, sorting out how to actually make this happen with the current and
	the new pass managers, understanding how and when to invalidate the Polly
	analysis and if dependence information can be computed on-demand make this
	still a challenging project. If successful, this project may be a great way
	to bring features of Polly to standard -O3 optimizations.

	<h3>Register tiling to obtain fast BLAS kernels with Polly</h3>
	Even though Polly is already able to speep up compute kernels significantly,
	when comparing to the best BLAS routines we still are at least one order of
	magnitude off. In this project you will investigate what is needed to close
	this performance gap. Earlier investigations have shown that register tiling
	is one important piece towards this goal. In combination with good tile size
	models and some back-end work, this project is shooting to make common blas
	operations, but also many non-blas kernels competitive with vendor math
	libraries and outperforming the code icc/gcc currently generate.

	<h3>Polly support for Julia - First steps</h3>
	<a href="http://julialang.org/">Julia</a> is a new matlab style programming
	language that provides C like performance for scientific computing. Even
	though Julia also translates to LLVM-IR, parsing and optimizing Julia code
	poses new challenges that currently prevent Polly from optimizing Julia
	code despite the clear need for optimizations such as loop-tiling for Julia.
	In this project you will -- starting from first proof-of-concept patches --
	integrate Polly into Julia and ensure that Julia code can benefit from the
	same high-level loop optimizations as todays C code already does. If time
	permits, making Polly's recent bound-check elimination logic work in Julia
	code would allow the optimization of Julia code, even if save out-of-bound
	checking is used.
	<h3>Interactive Polyhedral Web Calculator</h3>
	At the core of Polly we use the isl math library. isl allows us to describe
	loop transformations with relatively simple higher level operations while
	still providing the full expressiveness of integer polyhedra. To understand
	and describe the transformations we are performing it is often very convenient
	to quickly script example transformations in a scripting language like python.
	isl already comes with a python binding generator, with
	pypyjs there is a python interpreter for the web and with emscriptem isl
	itself can also be compiled to javascript. In this project you combine all
	these components to obtain an interactive polyhedral web calculator, that uses
	latest web technology to nicely illustrate the integer polyhedra you obtain.
	</div>
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	</body>
	</html>