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
Tobias Grosser