Currently, pattern based optimizations of Polly can identify matrix
multiplication and optimize it according to BLIS matmul optimization pattern
(see ScheduleTreeOptimizer for details). This patch makes optimizations
based on pattern matching be enabled by default.
Reviewed-by: Tobias Grosser <tobias@grosser.es>
Differential Revision: https://reviews.llvm.org/D30293
llvm-svn: 295958
These flags are now always passed to all tests and need to be disabled if
not needed. Disabling these flags, rather than passing them to almost all
tests, significantly simplfies our RUN: lines.
llvm-svn: 249422
Polly uses 'prevectorization' to enable outer loop vectorization. When
vectorizing an outer loop, we strip-mine <number-of-prevec-dims> loop
iterations which are than interchanged to the innermost level such that LLVM's
inner loop vectorizer (or Polly's simple vectorizer) can easily vectorize this
loop. The number of loop iterations to strip-mine is now configurable with the
option -polly-prevect-width=<number-of-prevec-dims>.
This is mostly a debugging option. We should probably add a heuristic that
derives the number of prevectorization dimensions from the target data and
the data types used.
llvm-svn: 245424
Schedule trees are a lot easier to work with, for both humans and machines. For
humans the more structured schedule representation is easier to reason about.
Together with the more abstract isl programming interface this can result in a
lot cleaner code (see this changeset). For machines, the structured schedule and
the fact that we now use explicit piecewise affine expressions instead of
integer maps makes it easier to generate code from this schedule tree. As a
result, we can already see a slight compile-time improvement -- for 3mm from
0m0.593s to 0m0.551s seconds (-7 %). More importantly, future optimizations such
as full-partial tile separation will most likely result in more streamlined code
to be generated.
Contributed-by: Roman Gareev <gareevroman@gmail.com>
llvm-svn: 243458
Instead of flat schedules, we now use so-called schedule trees to represent the
execution order of the statements in a SCoP. Schedule trees make it a lot easier
to analyze, understand and modify properties of a schedule, as specific nodes
in the tree can be choosen and possibly replaced.
This patch does not yet fully move our DependenceInfo pass to schedule trees,
as some additional performance analysis is needed here. (In general schedule
trees should be faster in compile-time, as the more structured representation
is generally easier to analyze and work with). We also can not yet perform the
reduction analysis on schedule trees.
For more information regarding schedule trees, please see Section 6 of
https://lirias.kuleuven.be/handle/123456789/497238
llvm-svn: 242130
I just learned that target triples prevent test cases to be run on other
architectures. Polly test cases are until now sufficiently target independent
to not require any target triples. Hence, we drop them.
llvm-svn: 235384
Replacing the old band_tree based code with code that is based on the new
schedule tree [1] interface makes applying complex schedule transformations a lot
more straightforward. We now do not need to reason about the meaning of flat
schedules, but can use a more straightforward tree structure. We do not yet
exploit this a lot in the current code, but hopefully we will be able to do so
soon.
This change also allows us to drop some code, as isl now provides some higher
level interfaces to apply loop transformations such as tiling.
This change causes some small test case changes as isl uses a slightly different
way to perform loop tiling, but no significant functional changes are intended.
[1] http://impact.gforge.inria.fr/impact2014/papers/impact2014-verdoolaege.pdf
llvm-svn: 232911
Scops that only read seem generally uninteresting and scops that only write are
most likely initializations where there is also little to optimize. To not
waste compile time we bail early.
Differential Revision: http://reviews.llvm.org/D7735
llvm-svn: 229820
We introduces a new flag -polly-parallel and use it to annotate the for-nodes in
the isl ast that we want to execute thread parallel (e.g., using OpenMP). We
previously already emmitted openmp annotations, but we did this for various
kinds of parallel loops, including some which we can not run in parallel.
With this patch we now have three annotations:
1) #pragma known-parallel [reduction]
2) #pragma omp for
3) #pragma simd
meaning:
1) loop has no loop carried dependences
2) loop will be executed thread-parallel
3) loop can possibly be vectorized
This patch introduces 1) and reduces the use of 2) to only the cases where we
will actually generate thread parallel code.
It is in preparation of openmp code generation in our isl backend.
Legacy:
- We also have a command line option -enable-polly-openmp. This option controls
the OpenMP code generation in CLooG. It will become an alias of
-polly-parallel after the CLooG code generation has been dropped.
http://reviews.llvm.org/D6142
llvm-svn: 221479
In case we are at the innermost band, we try to prepare for vectorization. This
means, we look for the innermost parallel loop and strip mine this loop to the
innermost level using a strip-mine factor corresponding to the number of vector
iterations.
For whatever reason, the code that implemented this feature was broken. We now
added a comment, a test case and obviously also the right code.
llvm-svn: 203544
Roman Gareev