VPlan-native path
Context: Patch Series #2 for outer loop vectorization support in LV
using VPlan. (RFC:
http://lists.llvm.org/pipermail/llvm-dev/2017-December/119523.html).
Patch series #2 checks that inner loops are still trivially lock-step
among all vector elements. Non-loop branches are blindly assumed as
divergent.
Changes here implement VPlan based predication algorithm to compute
predicates for blocks that need predication. Predicates are computed
for the VPLoop region in reverse post order. A block's predicate is
computed as OR of the masks of all incoming edges. The mask for an
incoming edge is computed as AND of predecessor block's predicate and
either predecessor's Condition bit or NOT(Condition bit) depending on
whether the edge from predecessor block to the current block is true
or false edge.
Reviewers: fhahn, rengolin, hsaito, dcaballe
Reviewed By: fhahn
Patch by Satish Guggilla, thanks!
Differential Revision: https://reviews.llvm.org/D53349
llvm-svn: 351990
This patch adds an initial implementation of the look-ahead SLP tree
construction described in 'Look-Ahead SLP: Auto-vectorization in the Presence
of Commutative Operations, CGO 2018 by Vasileios Porpodas, Rodrigo C. O. Rocha,
Luís F. W. Góes'.
It returns an SLP tree represented as VPInstructions, with combined
instructions represented as a single, wider VPInstruction.
This initial version does not support instructions with multiple
different users (either inside or outside the SLP tree) or
non-instruction operands; it won't generate any shuffles or
insertelement instructions.
It also just adds the analysis that builds an SLP tree rooted in a set
of stores. It does not include any cost modeling or memory legality
checks. The plan is to integrate it with VPlan based cost modeling, once
available and to only apply it to operations that can be widened.
A follow-up patch will add a support for replacing instructions in a
VPlan with their SLP counter parts.
Reviewers: Ayal, mssimpso, rengolin, mkuper, hfinkel, hsaito, dcaballe, vporpo, RKSimon, ABataev
Reviewed By: rengolin
Differential Revision: https://reviews.llvm.org/D4949
llvm-svn: 346857
This patch introduces a VPInstructionToVPRecipe transformation, which
allows us to generate code for a VPInstruction based VPlan re-using the
existing infrastructure.
Reviewers: dcaballe, hsaito, mssimpso, hfinkel, rengolin, mkuper, javed.absar, sguggill
Reviewed By: dcaballe
Differential Revision: https://reviews.llvm.org/D46827
llvm-svn: 334969
r332654 was reverted due to an unused function warning in
release build. This commit includes the same code with the
warning silenced.
Differential Revision: https://reviews.llvm.org/D44338
llvm-svn: 332860
The introduced problem is:
llvm.src/lib/Transforms/Vectorize/VPlanVerifier.cpp:29:13: error: unused function 'hasDuplicates' [-Werror,-Wunused-function]
static bool hasDuplicates(const SmallVectorImpl<VPBlockBase *> &VPBlockVec) {
^
llvm-svn: 332747
Patch #3 from VPlan Outer Loop Vectorization Patch Series #1
(RFC: http://lists.llvm.org/pipermail/llvm-dev/2017-December/119523.html).
Expected to be NFC for the current inner loop vectorization path. It
introduces the basic algorithm to build the VPlan plain CFG (single-level
CFG, no hierarchical CFG (H-CFG), yet) in the VPlan-native vectorization
path using VPInstructions. It includes:
- VPlanHCFGBuilder: Main class to build the VPlan H-CFG (plain CFG without nested regions, for now).
- VPlanVerifier: Main class with utilities to check the consistency of a H-CFG.
- VPlanBlockUtils: Main class with utilities to manipulate VPBlockBases in VPlan.
Reviewers: rengolin, fhahn, mkuper, mssimpso, a.elovikov, hfinkel, aprantl.
Differential Revision: https://reviews.llvm.org/D44338
llvm-svn: 332654
Summary:
This is a follow up to D45420 (included here since it is still under review and this change is dependent on that) and D45072 (committed).
Actual change for this patch is LoopVectorize* and cmakefile. All others are all from D45420.
LoopVectorizationLegality is an analysis and thus really belongs to Analysis tree. It is modular enough and it is reusable enough ---- we can further improve those aspects once uses outside of LV picks up.
Hopefully, this will make it easier for people familiar with vectorization theory, but not necessarily LV itself to contribute, by lowering the volume of code they should deal with. We probably should start adding some code in LV to check its own capability (i.e., vectorization is legal but LV is not ready to handle it) and then bail out.
Reviewers: rengolin, fhahn, hfinkel, mkuper, aemerson, mssimpso, dcaballe, sguggill
Reviewed By: rengolin, dcaballe
Subscribers: egarcia, rogfer01, mgorny, llvm-commits
Differential Revision: https://reviews.llvm.org/D45552
llvm-svn: 331139
Original commit r311077 of D32871 was reverted in r311304 due to failures
reported in PR34248.
This recommit fixes PR34248 by restricting the packing of predicated scalars
into vectors only when vectorizing, avoiding doing so when unrolling w/o
vectorizing. Added a test derived from the reproducer of PR34248.
llvm-svn: 311849
VPlan is an ongoing effort to refactor and extend the Loop Vectorizer. This
patch introduces the VPlan model into LV and uses it to represent the vectorized
code and drive the generation of vectorized IR.
In this patch VPlan models the vectorized loop body: the vectorized control-flow
is represented using VPlan's Hierarchical CFG, with predication refactored from
being a post-vectorization-step into a vectorization planning step modeling
if-then VPRegionBlocks, and generating code inline with non-predicated code. The
vectorized code within each VPBasicBlock is represented as a sequence of
Recipes, each responsible for modelling and generating a sequence of IR
instructions. To keep the size of this commit manageable the Recipes in this
patch are coarse-grained and capture large chunks of LV's code-generation logic.
The constructed VPlans are dumped in dot format under -debug.
This commit retains current vectorizer output, except for minor instruction
reorderings; see associated modifications to lit tests.
For further details on the VPlan model see docs/Proposals/VectorizationPlan.rst
and its references.
Authors: Gil Rapaport and Ayal Zaks
Differential Revision: https://reviews.llvm.org/D32871
llvm-svn: 311077
It served us well, helped kick-start much of the vectorization efforts
in LLVM, etc. Its time has come and past. Back in 2014:
http://lists.llvm.org/pipermail/llvm-dev/2014-November/079091.html
Time to actually let go and move forward. =]
I've updated the release notes both about the removal and the
deprecation of the corresponding C API.
llvm-svn: 306797
This patch updates a bunch of places where add_dependencies was being explicitly called to add dependencies on intrinsics_gen to instead use the DEPENDS named parameter. This cleanup is needed for a patch I'm working on to add a dependency debugging mode to the build system.
llvm-svn: 287206
This allows IDEs to recognize the entire set of header files for
each of the core LLVM projects.
Differential Revision: http://reviews.llvm.org/D7526
Reviewed By: Chris Bieneman
llvm-svn: 228798
Rewrote the SLP-vectorization as a whole-function vectorization pass. It is now able to vectorize chains across multiple basic blocks.
It still does not vectorize PHIs, but this should be easy to do now that we scan the entire function.
I removed the support for extracting values from trees.
We are now able to vectorize more programs, but there are some serious regressions in many workloads (such as flops-6 and mandel-2).
llvm-svn: 184647
This commit adds the infrastructure for performing bottom-up SLP vectorization (and other optimizations) on parallel computations.
The infrastructure has three potential users:
1. The loop vectorizer needs to be able to vectorize AOS data structures such as (sum += A[i] + A[i+1]).
2. The BB-vectorizer needs this infrastructure for bottom-up SLP vectorization, because bottom-up vectorization is faster to compute.
3. A loop-roller needs to be able to analyze consecutive chains and roll them into a loop, in order to reduce code size. A loop roller does not need to create vector instructions, and this infrastructure separates the chain analysis from the vectorization.
This patch also includes a simple (100 LOC) bottom up SLP vectorizer that uses the infrastructure, and can vectorize this code:
void SAXPY(int *x, int *y, int a, int i) {
x[i] = a * x[i] + y[i];
x[i+1] = a * x[i+1] + y[i+1];
x[i+2] = a * x[i+2] + y[i+2];
x[i+3] = a * x[i+3] + y[i+3];
}
llvm-svn: 179117
This is the initial checkin of the basic-block autovectorization pass along with some supporting vectorization infrastructure.
Special thanks to everyone who helped review this code over the last several months (especially Tobias Grosser).
llvm-svn: 149468
Hideki Saito