forked from OSchip/llvm-project
629 lines
24 KiB
C++
629 lines
24 KiB
C++
//===- 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.
|
||
//
|
||
//===----------------------------------------------------------------------===//
|
||
//
|
||
// 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 101–113. 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<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 don’t 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);
|
||
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;
|
||
}
|
||
|
||
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)
|