llvm-project/polly/lib/Transform/ScheduleOptimizer.cpp

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//===- Schedule.cpp - Calculate an optimized schedule ---------------------===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
//
AST Generation Paper published in TOPLAS 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
2015-08-15 17:34:33 +08:00
// This pass generates an entirey new schedule tree from the data dependences
// and iteration domains. The new schedule tree is computed in two steps:
//
// 1) The isl scheduling optimizer is run
//
// The isl scheduling optimizer creates a new schedule tree that maximizes
// parallelism and tileability and minimizes data-dependence distances. The
// algorithm used is a modified version of the ``Pluto'' algorithm:
//
// U. Bondhugula, A. Hartono, J. Ramanujam, and P. Sadayappan.
// A Practical Automatic Polyhedral Parallelizer and Locality Optimizer.
// In Proceedings of the 2008 ACM SIGPLAN Conference On Programming Language
// Design and Implementation, PLDI 08, pages 101113. ACM, 2008.
//
// 2) A set of post-scheduling transformations is applied on the schedule tree.
//
// These optimizations include:
//
// - Tiling of the innermost tilable bands
// - Prevectorization - The coice of a possible outer loop that is strip-mined
// to the innermost level to enable inner-loop
// vectorization.
// - Some optimizations for spatial locality are also planned.
//
// For a detailed description of the schedule tree itself please see section 6
// of:
//
// 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
// http://www.grosser.es/#pub-polyhedral-AST-generation
//
// This publication also contains a detailed discussion of the different options
// for polyhedral loop unrolling, full/partial tile separation and other uses
// of the schedule tree.
//
//===----------------------------------------------------------------------===//
#include "polly/ScheduleOptimizer.h"
#include "polly/CodeGen/CodeGeneration.h"
#include "polly/DependenceInfo.h"
#include "polly/LinkAllPasses.h"
#include "polly/Options.h"
#include "polly/ScopInfo.h"
#include "polly/Support/GICHelper.h"
#include "llvm/Support/Debug.h"
#include "isl/aff.h"
#include "isl/band.h"
#include "isl/constraint.h"
#include "isl/map.h"
#include "isl/options.h"
#include "isl/printer.h"
#include "isl/schedule.h"
#include "isl/schedule_node.h"
#include "isl/space.h"
#include "isl/union_map.h"
#include "isl/union_set.h"
using namespace llvm;
using namespace polly;
#define DEBUG_TYPE "polly-opt-isl"
static cl::opt<std::string>
OptimizeDeps("polly-opt-optimize-only",
cl::desc("Only a certain kind of dependences (all/raw)"),
cl::Hidden, cl::init("all"), cl::ZeroOrMore,
cl::cat(PollyCategory));
static cl::opt<std::string>
SimplifyDeps("polly-opt-simplify-deps",
cl::desc("Dependences should be simplified (yes/no)"),
cl::Hidden, cl::init("yes"), cl::ZeroOrMore,
cl::cat(PollyCategory));
static cl::opt<int> MaxConstantTerm(
"polly-opt-max-constant-term",
cl::desc("The maximal constant term allowed (-1 is unlimited)"), cl::Hidden,
cl::init(20), cl::ZeroOrMore, cl::cat(PollyCategory));
static cl::opt<int> MaxCoefficient(
"polly-opt-max-coefficient",
cl::desc("The maximal coefficient allowed (-1 is unlimited)"), cl::Hidden,
cl::init(20), cl::ZeroOrMore, cl::cat(PollyCategory));
static cl::opt<std::string> FusionStrategy(
"polly-opt-fusion", cl::desc("The fusion strategy to choose (min/max)"),
cl::Hidden, cl::init("min"), cl::ZeroOrMore, cl::cat(PollyCategory));
static cl::opt<std::string>
MaximizeBandDepth("polly-opt-maximize-bands",
cl::desc("Maximize the band depth (yes/no)"), cl::Hidden,
cl::init("yes"), cl::ZeroOrMore, cl::cat(PollyCategory));
static cl::opt<std::string> OuterCoincidence(
"polly-opt-outer-coincidence",
cl::desc("Try to construct schedules where the outer member of each band "
"satisfies the coincidence constraints (yes/no)"),
cl::Hidden, cl::init("no"), cl::ZeroOrMore, cl::cat(PollyCategory));
static cl::opt<int> PrevectorWidth(
"polly-prevect-width",
cl::desc(
"The number of loop iterations to strip-mine for pre-vectorization"),
cl::Hidden, cl::init(4), cl::ZeroOrMore, cl::cat(PollyCategory));
static cl::opt<bool> FirstLevelTiling("polly-tiling",
cl::desc("Enable loop tiling"),
cl::init(true), cl::ZeroOrMore,
cl::cat(PollyCategory));
static cl::opt<int> FirstLevelDefaultTileSize(
"polly-default-tile-size",
cl::desc("The default tile size (if not enough were provided by"
" --polly-tile-sizes)"),
cl::Hidden, cl::init(32), cl::ZeroOrMore, cl::cat(PollyCategory));
static cl::list<int> FirstLevelTileSizes(
"polly-tile-sizes", cl::desc("A tile size for each loop dimension, filled "
"with --polly-default-tile-size"),
cl::Hidden, cl::ZeroOrMore, cl::CommaSeparated, cl::cat(PollyCategory));
static cl::opt<bool>
SecondLevelTiling("polly-2nd-level-tiling",
cl::desc("Enable a 2nd level loop of loop tiling"),
cl::init(false), cl::ZeroOrMore, cl::cat(PollyCategory));
static cl::opt<int> SecondLevelDefaultTileSize(
"polly-2nd-level-default-tile-size",
cl::desc("The default 2nd-level tile size (if not enough were provided by"
" --polly-2nd-level-tile-sizes)"),
cl::Hidden, cl::init(16), cl::ZeroOrMore, cl::cat(PollyCategory));
static cl::list<int>
SecondLevelTileSizes("polly-2nd-level-tile-sizes",
cl::desc("A tile size for each loop dimension, filled "
"with --polly-default-tile-size"),
cl::Hidden, cl::ZeroOrMore, cl::CommaSeparated,
cl::cat(PollyCategory));
static cl::opt<bool> RegisterTiling("polly-register-tiling",
cl::desc("Enable register tiling"),
cl::init(false), cl::ZeroOrMore,
cl::cat(PollyCategory));
static cl::opt<int> RegisterDefaultTileSize(
"polly-register-tiling-default-tile-size",
cl::desc("The default register tile size (if not enough were provided by"
" --polly-register-tile-sizes)"),
cl::Hidden, cl::init(2), cl::ZeroOrMore, cl::cat(PollyCategory));
static cl::list<int>
RegisterTileSizes("polly-register-tile-sizes",
cl::desc("A tile size for each loop dimension, filled "
"with --polly-register-tile-size"),
cl::Hidden, cl::ZeroOrMore, cl::CommaSeparated,
cl::cat(PollyCategory));
/// @brief Create an isl_union_set, which describes the isolate option based
/// on IsoalteDomain.
///
/// @param IsolateDomain An isl_set whose last dimension is the only one that
/// should belong to the current band node.
static __isl_give isl_union_set *
getIsolateOptions(__isl_take isl_set *IsolateDomain) {
auto Dims = isl_set_dim(IsolateDomain, isl_dim_set);
auto *IsolateRelation = isl_map_from_domain(IsolateDomain);
IsolateRelation = isl_map_move_dims(IsolateRelation, isl_dim_out, 0,
isl_dim_in, Dims - 1, 1);
auto *IsolateOption = isl_map_wrap(IsolateRelation);
auto *Id = isl_id_alloc(isl_set_get_ctx(IsolateOption), "isolate", NULL);
return isl_union_set_from_set(isl_set_set_tuple_id(IsolateOption, Id));
}
/// @brief Create an isl_union_set, which describes the atomic option for the
/// dimension of the current node.
///
/// It may help to reduce the size of generated code.
///
/// @param Ctx An isl_ctx, which is used to create the isl_union_set.
static __isl_give isl_union_set *getAtomicOptions(__isl_take isl_ctx *Ctx) {
auto *Space = isl_space_set_alloc(Ctx, 0, 1);
auto *AtomicOption = isl_set_universe(Space);
auto *Id = isl_id_alloc(Ctx, "atomic", NULL);
return isl_union_set_from_set(isl_set_set_tuple_id(AtomicOption, Id));
}
/// @brief Make the last dimension of Set to take values
/// from 0 to VectorWidth - 1.
///
/// @param Set A set, which should be modified.
/// @param VectorWidth A parameter, which determines the constraint.
static __isl_give isl_set *addExtentConstraints(__isl_take isl_set *Set,
int VectorWidth) {
auto Dims = isl_set_dim(Set, isl_dim_set);
auto Space = isl_set_get_space(Set);
auto *LocalSpace = isl_local_space_from_space(Space);
auto *ExtConstr =
isl_constraint_alloc_inequality(isl_local_space_copy(LocalSpace));
ExtConstr = isl_constraint_set_constant_si(ExtConstr, 0);
ExtConstr =
isl_constraint_set_coefficient_si(ExtConstr, isl_dim_set, Dims - 1, 1);
Set = isl_set_add_constraint(Set, ExtConstr);
ExtConstr = isl_constraint_alloc_inequality(LocalSpace);
ExtConstr = isl_constraint_set_constant_si(ExtConstr, VectorWidth - 1);
ExtConstr =
isl_constraint_set_coefficient_si(ExtConstr, isl_dim_set, Dims - 1, -1);
return isl_set_add_constraint(Set, ExtConstr);
}
/// @brief Build the desired set of partial tile prefixes.
///
/// We build a set of partial tile prefixes, which are prefixes of the vector
/// loop that have exactly VectorWidth iterations.
///
/// 1. Get all prefixes of the vector loop.
/// 2. Extend it to a set, which has exactly VectorWidth iterations for
/// any prefix from the set that was built on the previous step.
/// 3. Subtract loop domain from it, project out the vector loop dimension and
/// get a set of prefixes, which dont have exactly VectorWidth iterations.
/// 4. Subtract it from all prefixes of the vector loop and get the desired
/// set.
///
/// @param ScheduleRange A range of a map, which describes a prefix schedule
/// relation.
static __isl_give isl_set *
getPartialTilePrefixes(__isl_take isl_set *ScheduleRange, int VectorWidth) {
auto Dims = isl_set_dim(ScheduleRange, isl_dim_set);
auto *LoopPrefixes = isl_set_project_out(isl_set_copy(ScheduleRange),
isl_dim_set, Dims - 1, 1);
auto *ExtentPrefixes =
isl_set_add_dims(isl_set_copy(LoopPrefixes), isl_dim_set, 1);
ExtentPrefixes = addExtentConstraints(ExtentPrefixes, VectorWidth);
auto *BadPrefixes = isl_set_subtract(ExtentPrefixes, ScheduleRange);
BadPrefixes = isl_set_project_out(BadPrefixes, isl_dim_set, Dims - 1, 1);
return isl_set_subtract(LoopPrefixes, BadPrefixes);
}
__isl_give isl_schedule_node *ScheduleTreeOptimizer::isolateFullPartialTiles(
__isl_take isl_schedule_node *Node, int VectorWidth) {
assert(isl_schedule_node_get_type(Node) == isl_schedule_node_band);
Node = isl_schedule_node_child(Node, 0);
Node = isl_schedule_node_child(Node, 0);
auto *SchedRelUMap = isl_schedule_node_get_prefix_schedule_relation(Node);
auto *ScheduleRelation = isl_map_from_union_map(SchedRelUMap);
auto *ScheduleRange = isl_map_range(ScheduleRelation);
auto *IsolateDomain = getPartialTilePrefixes(ScheduleRange, VectorWidth);
auto *AtomicOption = getAtomicOptions(isl_set_get_ctx(IsolateDomain));
auto *IsolateOption = getIsolateOptions(IsolateDomain);
Node = isl_schedule_node_parent(Node);
Node = isl_schedule_node_parent(Node);
auto *Options = isl_union_set_union(IsolateOption, AtomicOption);
Node = isl_schedule_node_band_set_ast_build_options(Node, Options);
return Node;
}
__isl_give isl_schedule_node *
ScheduleTreeOptimizer::prevectSchedBand(__isl_take isl_schedule_node *Node,
unsigned DimToVectorize,
int VectorWidth) {
assert(isl_schedule_node_get_type(Node) == isl_schedule_node_band);
auto Space = isl_schedule_node_band_get_space(Node);
auto ScheduleDimensions = isl_space_dim(Space, isl_dim_set);
isl_space_free(Space);
assert(DimToVectorize < ScheduleDimensions);
if (DimToVectorize > 0) {
Node = isl_schedule_node_band_split(Node, DimToVectorize);
Node = isl_schedule_node_child(Node, 0);
}
if (DimToVectorize < ScheduleDimensions - 1)
Node = isl_schedule_node_band_split(Node, 1);
Space = isl_schedule_node_band_get_space(Node);
auto Sizes = isl_multi_val_zero(Space);
auto Ctx = isl_schedule_node_get_ctx(Node);
Sizes =
isl_multi_val_set_val(Sizes, 0, isl_val_int_from_si(Ctx, VectorWidth));
Node = isl_schedule_node_band_tile(Node, Sizes);
Node = isolateFullPartialTiles(Node, VectorWidth);
Node = isl_schedule_node_child(Node, 0);
// Make sure the "trivially vectorizable loop" is not unrolled. Otherwise,
// we will have troubles to match it in the backend.
Node = isl_schedule_node_band_set_ast_build_options(
Node, isl_union_set_read_from_str(Ctx, "{ unroll[x]: 1 = 0 }"));
Node = isl_schedule_node_band_sink(Node);
Node = isl_schedule_node_child(Node, 0);
if (isl_schedule_node_get_type(Node) == isl_schedule_node_leaf)
Node = isl_schedule_node_parent(Node);
isl_id *LoopMarker = isl_id_alloc(Ctx, "SIMD", nullptr);
Node = isl_schedule_node_insert_mark(Node, LoopMarker);
return Node;
}
__isl_give isl_schedule_node *
ScheduleTreeOptimizer::tileNode(__isl_take isl_schedule_node *Node,
const char *Identifier, ArrayRef<int> TileSizes,
int DefaultTileSize) {
auto Ctx = isl_schedule_node_get_ctx(Node);
auto Space = isl_schedule_node_band_get_space(Node);
auto Dims = isl_space_dim(Space, isl_dim_set);
auto Sizes = isl_multi_val_zero(Space);
std::string IdentifierString(Identifier);
for (unsigned i = 0; i < Dims; i++) {
auto tileSize = i < TileSizes.size() ? TileSizes[i] : DefaultTileSize;
Sizes = isl_multi_val_set_val(Sizes, i, isl_val_int_from_si(Ctx, tileSize));
}
auto TileLoopMarkerStr = IdentifierString + " - Tiles";
isl_id *TileLoopMarker =
isl_id_alloc(Ctx, TileLoopMarkerStr.c_str(), nullptr);
Node = isl_schedule_node_insert_mark(Node, TileLoopMarker);
Node = isl_schedule_node_child(Node, 0);
Node = isl_schedule_node_band_tile(Node, Sizes);
Node = isl_schedule_node_child(Node, 0);
auto PointLoopMarkerStr = IdentifierString + " - Points";
isl_id *PointLoopMarker =
isl_id_alloc(Ctx, PointLoopMarkerStr.c_str(), nullptr);
Node = isl_schedule_node_insert_mark(Node, PointLoopMarker);
Node = isl_schedule_node_child(Node, 0);
return Node;
}
bool ScheduleTreeOptimizer::isTileableBandNode(
__isl_keep isl_schedule_node *Node) {
if (isl_schedule_node_get_type(Node) != isl_schedule_node_band)
return false;
if (isl_schedule_node_n_children(Node) != 1)
return false;
if (!isl_schedule_node_band_get_permutable(Node))
return false;
auto Space = isl_schedule_node_band_get_space(Node);
auto Dims = isl_space_dim(Space, isl_dim_set);
isl_space_free(Space);
if (Dims <= 1)
return false;
auto Child = isl_schedule_node_get_child(Node, 0);
auto Type = isl_schedule_node_get_type(Child);
isl_schedule_node_free(Child);
if (Type != isl_schedule_node_leaf)
return false;
return true;
}
__isl_give isl_schedule_node *
ScheduleTreeOptimizer::optimizeBand(__isl_take isl_schedule_node *Node,
void *User) {
if (!isTileableBandNode(Node))
return Node;
if (FirstLevelTiling)
Node = tileNode(Node, "1st level tiling", FirstLevelTileSizes,
FirstLevelDefaultTileSize);
if (SecondLevelTiling)
Node = tileNode(Node, "2nd level tiling", SecondLevelTileSizes,
SecondLevelDefaultTileSize);
if (RegisterTiling) {
auto *Ctx = isl_schedule_node_get_ctx(Node);
Node = tileNode(Node, "Register tiling", RegisterTileSizes,
RegisterDefaultTileSize);
Node = isl_schedule_node_band_set_ast_build_options(
Node, isl_union_set_read_from_str(Ctx, "{unroll[x]}"));
}
if (PollyVectorizerChoice == VECTORIZER_NONE)
return Node;
auto Space = isl_schedule_node_band_get_space(Node);
auto Dims = isl_space_dim(Space, isl_dim_set);
isl_space_free(Space);
for (int i = Dims - 1; i >= 0; i--)
if (isl_schedule_node_band_member_get_coincident(Node, i)) {
Node = prevectSchedBand(Node, i, PrevectorWidth);
break;
}
return Node;
}
__isl_give isl_schedule *
ScheduleTreeOptimizer::optimizeSchedule(__isl_take isl_schedule *Schedule) {
isl_schedule_node *Root = isl_schedule_get_root(Schedule);
Root = optimizeScheduleNode(Root);
isl_schedule_free(Schedule);
auto S = isl_schedule_node_get_schedule(Root);
isl_schedule_node_free(Root);
return S;
}
__isl_give isl_schedule_node *ScheduleTreeOptimizer::optimizeScheduleNode(
__isl_take isl_schedule_node *Node) {
Node = isl_schedule_node_map_descendant_bottom_up(Node, optimizeBand, NULL);
return Node;
}
bool ScheduleTreeOptimizer::isProfitableSchedule(
Scop &S, __isl_keep isl_union_map *NewSchedule) {
// To understand if the schedule has been optimized we check if the schedule
// has changed at all.
// TODO: We can improve this by tracking if any necessarily beneficial
// transformations have been performed. This can e.g. be tiling, loop
// interchange, or ...) We can track this either at the place where the
// transformation has been performed or, in case of automatic ILP based
// optimizations, by comparing (yet to be defined) performance metrics
// before/after the scheduling optimizer
// (e.g., #stride-one accesses)
isl_union_map *OldSchedule = S.getSchedule();
bool changed = !isl_union_map_is_equal(OldSchedule, NewSchedule);
isl_union_map_free(OldSchedule);
return changed;
}
namespace {
class IslScheduleOptimizer : public ScopPass {
public:
static char ID;
explicit IslScheduleOptimizer() : ScopPass(ID) { LastSchedule = nullptr; }
~IslScheduleOptimizer() { isl_schedule_free(LastSchedule); }
/// @brief Optimize the schedule of the SCoP @p S.
bool runOnScop(Scop &S) override;
/// @brief Print the new schedule for the SCoP @p S.
void printScop(raw_ostream &OS, Scop &S) const override;
/// @brief Register all analyses and transformation required.
void getAnalysisUsage(AnalysisUsage &AU) const override;
/// @brief Release the internal memory.
void releaseMemory() override {
isl_schedule_free(LastSchedule);
LastSchedule = nullptr;
}
private:
isl_schedule *LastSchedule;
};
}
char IslScheduleOptimizer::ID = 0;
bool IslScheduleOptimizer::runOnScop(Scop &S) {
// Skip empty SCoPs but still allow code generation as it will delete the
// loops present but not needed.
if (S.getSize() == 0) {
S.markAsOptimized();
return false;
}
const Dependences &D =
getAnalysis<DependenceInfo>().getDependences(Dependences::AL_Statement);
if (!D.hasValidDependences())
return false;
isl_schedule_free(LastSchedule);
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LastSchedule = nullptr;
// Build input data.
int ValidityKinds =
Dependences::TYPE_RAW | Dependences::TYPE_WAR | Dependences::TYPE_WAW;
int ProximityKinds;
if (OptimizeDeps == "all")
ProximityKinds =
Dependences::TYPE_RAW | Dependences::TYPE_WAR | Dependences::TYPE_WAW;
else if (OptimizeDeps == "raw")
ProximityKinds = Dependences::TYPE_RAW;
else {
errs() << "Do not know how to optimize for '" << OptimizeDeps << "'"
<< " Falling back to optimizing all dependences.\n";
ProximityKinds =
Dependences::TYPE_RAW | Dependences::TYPE_WAR | Dependences::TYPE_WAW;
}
isl_union_set *Domain = S.getDomains();
if (!Domain)
return false;
isl_union_map *Validity = D.getDependences(ValidityKinds);
isl_union_map *Proximity = D.getDependences(ProximityKinds);
// Simplify the dependences by removing the constraints introduced by the
// domains. This can speed up the scheduling time significantly, as large
// constant coefficients will be removed from the dependences. The
// introduction of some additional dependences reduces the possible
// transformations, but in most cases, such transformation do not seem to be
// interesting anyway. In some cases this option may stop the scheduler to
// find any schedule.
if (SimplifyDeps == "yes") {
Validity = isl_union_map_gist_domain(Validity, isl_union_set_copy(Domain));
Validity = isl_union_map_gist_range(Validity, isl_union_set_copy(Domain));
Proximity =
isl_union_map_gist_domain(Proximity, isl_union_set_copy(Domain));
Proximity = isl_union_map_gist_range(Proximity, isl_union_set_copy(Domain));
} else if (SimplifyDeps != "no") {
errs() << "warning: Option -polly-opt-simplify-deps should either be 'yes' "
"or 'no'. Falling back to default: 'yes'\n";
}
DEBUG(dbgs() << "\n\nCompute schedule from: ");
DEBUG(dbgs() << "Domain := " << stringFromIslObj(Domain) << ";\n");
DEBUG(dbgs() << "Proximity := " << stringFromIslObj(Proximity) << ";\n");
DEBUG(dbgs() << "Validity := " << stringFromIslObj(Validity) << ";\n");
unsigned IslSerializeSCCs;
if (FusionStrategy == "max") {
IslSerializeSCCs = 0;
} else if (FusionStrategy == "min") {
IslSerializeSCCs = 1;
} else {
errs() << "warning: Unknown fusion strategy. Falling back to maximal "
"fusion.\n";
IslSerializeSCCs = 0;
}
int IslMaximizeBands;
if (MaximizeBandDepth == "yes") {
IslMaximizeBands = 1;
} else if (MaximizeBandDepth == "no") {
IslMaximizeBands = 0;
} else {
errs() << "warning: Option -polly-opt-maximize-bands should either be 'yes'"
" or 'no'. Falling back to default: 'yes'\n";
IslMaximizeBands = 1;
}
int IslOuterCoincidence;
if (OuterCoincidence == "yes") {
IslOuterCoincidence = 1;
} else if (OuterCoincidence == "no") {
IslOuterCoincidence = 0;
} else {
errs() << "warning: Option -polly-opt-outer-coincidence should either be "
"'yes' or 'no'. Falling back to default: 'no'\n";
IslOuterCoincidence = 0;
}
isl_options_set_schedule_outer_coincidence(S.getIslCtx(),
IslOuterCoincidence);
isl_options_set_schedule_serialize_sccs(S.getIslCtx(), IslSerializeSCCs);
isl_options_set_schedule_maximize_band_depth(S.getIslCtx(), IslMaximizeBands);
isl_options_set_schedule_max_constant_term(S.getIslCtx(), MaxConstantTerm);
isl_options_set_schedule_max_coefficient(S.getIslCtx(), MaxCoefficient);
isl_options_set_tile_scale_tile_loops(S.getIslCtx(), 0);
isl_options_set_on_error(S.getIslCtx(), ISL_ON_ERROR_CONTINUE);
isl_schedule_constraints *ScheduleConstraints;
ScheduleConstraints = isl_schedule_constraints_on_domain(Domain);
ScheduleConstraints =
isl_schedule_constraints_set_proximity(ScheduleConstraints, Proximity);
ScheduleConstraints = isl_schedule_constraints_set_validity(
ScheduleConstraints, isl_union_map_copy(Validity));
ScheduleConstraints =
isl_schedule_constraints_set_coincidence(ScheduleConstraints, Validity);
isl_schedule *Schedule;
Schedule = isl_schedule_constraints_compute_schedule(ScheduleConstraints);
isl_options_set_on_error(S.getIslCtx(), ISL_ON_ERROR_ABORT);
// In cases the scheduler is not able to optimize the code, we just do not
// touch the schedule.
if (!Schedule)
return false;
DEBUG({
auto *P = isl_printer_to_str(S.getIslCtx());
P = isl_printer_set_yaml_style(P, ISL_YAML_STYLE_BLOCK);
P = isl_printer_print_schedule(P, Schedule);
dbgs() << "NewScheduleTree: \n" << isl_printer_get_str(P) << "\n";
isl_printer_free(P);
});
isl_schedule *NewSchedule = ScheduleTreeOptimizer::optimizeSchedule(Schedule);
isl_union_map *NewScheduleMap = isl_schedule_get_map(NewSchedule);
if (!ScheduleTreeOptimizer::isProfitableSchedule(S, NewScheduleMap)) {
isl_union_map_free(NewScheduleMap);
isl_schedule_free(NewSchedule);
return false;
}
S.setScheduleTree(NewSchedule);
S.markAsOptimized();
isl_union_map_free(NewScheduleMap);
return false;
}
void IslScheduleOptimizer::printScop(raw_ostream &OS, Scop &) const {
isl_printer *p;
char *ScheduleStr;
OS << "Calculated schedule:\n";
if (!LastSchedule) {
OS << "n/a\n";
return;
}
p = isl_printer_to_str(isl_schedule_get_ctx(LastSchedule));
p = isl_printer_print_schedule(p, LastSchedule);
ScheduleStr = isl_printer_get_str(p);
isl_printer_free(p);
OS << ScheduleStr << "\n";
}
void IslScheduleOptimizer::getAnalysisUsage(AnalysisUsage &AU) const {
ScopPass::getAnalysisUsage(AU);
AU.addRequired<DependenceInfo>();
}
Pass *polly::createIslScheduleOptimizerPass() {
return new IslScheduleOptimizer();
}
INITIALIZE_PASS_BEGIN(IslScheduleOptimizer, "polly-opt-isl",
"Polly - Optimize schedule of SCoP", false, false);
INITIALIZE_PASS_DEPENDENCY(DependenceInfo);
INITIALIZE_PASS_DEPENDENCY(ScopInfo);
INITIALIZE_PASS_END(IslScheduleOptimizer, "polly-opt-isl",
"Polly - Optimize schedule of SCoP", false, false)