Remove examples 'load_Polly_into_clang' and 'manual_matmul'. This information is
now available in our SPHINX docs (*).
(*) Thanks to Singapuram Sanjay Srivallabh <singapuram.sanjay@gmail.com> who
contributed the SPHINX docs update!
llvm-svn: 305186
The LLVM bug tracker is now available at bugs.llvm.org instead of llvm.org/bugs.
By updating our links to the tracker we do not only avoid unnecessary redirects,
but also certificate warnings.
We use this opportunity to shorten the text and to rename the link 'open bugs'
to 'show open bugs' to clearify its meaning.
llvm-svn: 304768
http://polly.llvm.org/example_manual_matmul.html which illustrates individual
passes of Polly, has been ported to reStructuredText and necessary changes have
been made to the configuration files used by SPHINX to include the new source as
a part of the documentation.
Contributed-by: Singapuram Sanjay Srivallabh <singapuram.sanjay@gmail.com>
Differential Revision: https://reviews.llvm.org/D25163
llvm-svn: 294735
Even though the commands still work, dragonegg has not been updated to work with
recent versions of LLVM. Consequently, only very old Polly versions (which we
do not support any more), can be used in this way.
This simplifies our documentation page.
llvm-svn: 259758
We remove information for older versions of Polly and also shorten the overall
text. This should make it a lot easier for people to get to the important code
wight away.
llvm-svn: 259658
The autotools build system is based on and requires LLVM's autotools
build system to work, which has been depricated and finally removed in
r258861. Consequently we also remove the autotools build system from
Polly.
Differential Revision: http://reviews.llvm.org/D16655
llvm-svn: 259041
Polly recently got its own product in LLVM's bug tracker, which will make it
easier for people to file Polly bugs. This change updates the bugtracker links
on the Polly website.
llvm-svn: 258494
The July issue of TOPLAS contains a 50 page discussion of the AST generation
techniques used in Polly. This discussion gives not only an in-depth
description of how we (re)generate an imperative AST from our polyhedral based
mathematical program description, but also gives interesting insights about:
- Schedule trees: A tree-based mathematical program description that enables us
to perform loop transformations on an abstract level, while issues like the
generation of the correct loop structure and loop bounds will be taken care of
by our AST generator.
- Polyhedral unrolling: We discuss techniques that allow the unrolling of
non-trivial loops in the context of parameteric loop bounds, complex tile
shapes and conditionally executed statements. Such unrolling support enables
the generation of predicated code e.g. in the context of GPGPU computing.
- Isolation for full/partial tile separation: We discuss native support for
handling full/partial tile separation and -- in general -- native support for
isolation of boundary cases to enable smooth code generation for core
computations.
- AST generation with modulo constraints: We discuss how modulo mappings are
lowered to efficient C/LLVM code.
- User-defined constraint sets for run-time checks We discuss how arbitrary
sets of constraints can be used to automatically create run-time checks that
ensure a set of constrainst actually hold. This feature is very useful to
verify at run-time various assumptions that have been taken program
optimization.
Polyhedral AST generation is more than scanning polyhedra
Tobias Grosser, Sven Verdoolaege, Albert Cohen
ACM Transations on Programming Languages and Systems (TOPLAS), 37(4), July 2015
llvm-svn: 245157
Philip Pfaffe