Open Projects

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 Google Summer of Code projects. In case you are interested in a Google Summer of code project make sure to reach out via the Polly mailing list early to discuss your project proposal.

Integrate Polly with the LLVM vectorizers

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.

Register tiling to obtain fast BLAS kernels with Polly

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.

Polly support for Julia - First steps

Julia 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.

Interactive Polyhedral Web Calculator

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.