forked from OSchip/llvm-project
88 lines
4.9 KiB
HTML
88 lines
4.9 KiB
HTML
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<META http-equiv="Content-Type" content="text/html; charset=ISO-8859-1">
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<title>Polly - Polyhedral optimizations for LLVM</title>
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<div id="content">
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<h1>Open Projects</h1>
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LLVM Polly keeps here a list of open projects which each of themselves would
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be a great contribution to Polly. All of these projects are meant to be self
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contained and should take a newcomer around 3-4 months of work. The projects
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we propose are all suiteable as <a
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href="https://developers.google.com/open-source/gsoc/">Google Summer of
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Code</a> projects. In case you are interested in a Google Summer of code
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project make sure to reach out via the Polly <a
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href="http://groups.google.com/group/polly-dev">mailing list</a> early to
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discuss your project proposal.
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<h3>Integrate Polly with the LLVM vectorizers</h3>
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Polly is not only a self-contained optimizer, but also provides a powerful
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dependence and other program analyses. Currently, these analyses are only used
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for our own optimizations. However, LLVM passes such as the loop vectorizer
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would clearly benefit from having direct access to the available Polly
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analyses. In this project, you would define in collaboration with the LLVM
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community and considering existing dependence analysis interface a new
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dependence analysis interface for Polly that allows passes to directly query
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Polly analysis. Even though this project sounds straightforward at a first
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glance, sorting out how to actually make this happen with the current and
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the new pass managers, understanding how and when to invalidate the Polly
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analysis and if dependence information can be computed on-demand make this
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still a challenging project. If successful, this project may be a great way
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to bring features of Polly to standard -O3 optimizations.
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<h3>Register tiling to obtain fast BLAS kernels with Polly</h3>
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Even though Polly is already able to speep up compute kernels significantly,
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when comparing to the best BLAS routines we still are at least one order of
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magnitude off. In this project you will investigate what is needed to close
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this performance gap. Earlier investigations have shown that register tiling
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is one important piece towards this goal. In combination with good tile size
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models and some back-end work, this project is shooting to make common blas
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operations, but also many non-blas kernels competitive with vendor math
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libraries and outperforming the code icc/gcc currently generate.
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<h3>Polly support for Julia - First steps</h3>
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<a href="http://julialang.org/">Julia</a> is a new matlab style programming
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language that provides C like performance for scientific computing. Even
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though Julia also translates to LLVM-IR, parsing and optimizing Julia code
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poses new challenges that currently prevent Polly from optimizing Julia
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code despite the clear need for optimizations such as loop-tiling for Julia.
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In this project you will -- starting from first proof-of-concept patches --
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integrate Polly into Julia and ensure that Julia code can benefit from the
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same high-level loop optimizations as todays C code already does. If time
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permits, making Polly's recent bound-check elimination logic work in Julia
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code would allow the optimization of Julia code, even if save out-of-bound
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checking is used.
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<h3>Interactive Polyhedral Web Calculator</h3>
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At the core of Polly we use the isl math library. isl allows us to describe
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loop transformations with relatively simple higher level operations while
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still providing the full expressiveness of integer polyhedra. To understand
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and describe the transformations we are performing it is often very convenient
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to quickly script example transformations in a scripting language like python.
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isl already comes with a python binding generator, with
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pypyjs there is a python interpreter for the web and with emscriptem isl
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itself can also be compiled to javascript. In this project you combine all
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these components to obtain an interactive polyhedral web calculator, that uses
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latest web technology to nicely illustrate the integer polyhedra you obtain.
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