1 //===------ FlattenAlgo.cpp ------------------------------------*- C++ -*-===// 2 // 3 // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. 4 // See https://llvm.org/LICENSE.txt for license information. 5 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception 6 // 7 //===----------------------------------------------------------------------===// 8 // 9 // Main algorithm of the FlattenSchedulePass. This is a separate file to avoid 10 // the unittest for this requiring linking against LLVM. 11 // 12 //===----------------------------------------------------------------------===// 13 14 #include "polly/FlattenAlgo.h" 15 #include "polly/Support/ISLOStream.h" 16 #include "polly/Support/ISLTools.h" 17 #include "llvm/Support/Debug.h" 18 #define DEBUG_TYPE "polly-flatten-algo" 19 20 using namespace polly; 21 using namespace llvm; 22 23 namespace { 24 25 /// Whether a dimension of a set is bounded (lower and upper) by a constant, 26 /// i.e. there are two constants Min and Max, such that every value x of the 27 /// chosen dimensions is Min <= x <= Max. 28 bool isDimBoundedByConstant(isl::set Set, unsigned dim) { 29 auto ParamDims = unsignedFromIslSize(Set.dim(isl::dim::param)); 30 Set = Set.project_out(isl::dim::param, 0, ParamDims); 31 Set = Set.project_out(isl::dim::set, 0, dim); 32 auto SetDims = unsignedFromIslSize(Set.tuple_dim()); 33 assert(SetDims >= 1); 34 Set = Set.project_out(isl::dim::set, 1, SetDims - 1); 35 return bool(Set.is_bounded()); 36 } 37 38 /// Whether a dimension of a set is (lower and upper) bounded by a constant or 39 /// parameters, i.e. there are two expressions Min_p and Max_p of the parameters 40 /// p, such that every value x of the chosen dimensions is 41 /// Min_p <= x <= Max_p. 42 bool isDimBoundedByParameter(isl::set Set, unsigned dim) { 43 Set = Set.project_out(isl::dim::set, 0, dim); 44 auto SetDims = unsignedFromIslSize(Set.tuple_dim()); 45 assert(SetDims >= 1); 46 Set = Set.project_out(isl::dim::set, 1, SetDims - 1); 47 return bool(Set.is_bounded()); 48 } 49 50 /// Whether BMap's first out-dimension is not a constant. 51 bool isVariableDim(const isl::basic_map &BMap) { 52 auto FixedVal = BMap.plain_get_val_if_fixed(isl::dim::out, 0); 53 return FixedVal.is_null() || FixedVal.is_nan(); 54 } 55 56 /// Whether Map's first out dimension is no constant nor piecewise constant. 57 bool isVariableDim(const isl::map &Map) { 58 for (isl::basic_map BMap : Map.get_basic_map_list()) 59 if (isVariableDim(BMap)) 60 return false; 61 62 return true; 63 } 64 65 /// Whether UMap's first out dimension is no (piecewise) constant. 66 bool isVariableDim(const isl::union_map &UMap) { 67 for (isl::map Map : UMap.get_map_list()) 68 if (isVariableDim(Map)) 69 return false; 70 return true; 71 } 72 73 /// Compute @p UPwAff - @p Val. 74 isl::union_pw_aff subtract(isl::union_pw_aff UPwAff, isl::val Val) { 75 if (Val.is_zero()) 76 return UPwAff; 77 78 auto Result = isl::union_pw_aff::empty(UPwAff.get_space()); 79 isl::stat Stat = 80 UPwAff.foreach_pw_aff([=, &Result](isl::pw_aff PwAff) -> isl::stat { 81 auto ValAff = 82 isl::pw_aff(isl::set::universe(PwAff.get_space().domain()), Val); 83 auto Subtracted = PwAff.sub(ValAff); 84 Result = Result.union_add(isl::union_pw_aff(Subtracted)); 85 return isl::stat::ok(); 86 }); 87 if (Stat.is_error()) 88 return {}; 89 return Result; 90 } 91 92 /// Compute @UPwAff * @p Val. 93 isl::union_pw_aff multiply(isl::union_pw_aff UPwAff, isl::val Val) { 94 if (Val.is_one()) 95 return UPwAff; 96 97 auto Result = isl::union_pw_aff::empty(UPwAff.get_space()); 98 isl::stat Stat = 99 UPwAff.foreach_pw_aff([=, &Result](isl::pw_aff PwAff) -> isl::stat { 100 auto ValAff = 101 isl::pw_aff(isl::set::universe(PwAff.get_space().domain()), Val); 102 auto Multiplied = PwAff.mul(ValAff); 103 Result = Result.union_add(Multiplied); 104 return isl::stat::ok(); 105 }); 106 if (Stat.is_error()) 107 return {}; 108 return Result; 109 } 110 111 /// Remove @p n dimensions from @p UMap's range, starting at @p first. 112 /// 113 /// It is assumed that all maps in the maps have at least the necessary number 114 /// of out dimensions. 115 isl::union_map scheduleProjectOut(const isl::union_map &UMap, unsigned first, 116 unsigned n) { 117 if (n == 0) 118 return UMap; /* isl_map_project_out would also reset the tuple, which should 119 have no effect on schedule ranges */ 120 121 auto Result = isl::union_map::empty(UMap.ctx()); 122 for (isl::map Map : UMap.get_map_list()) { 123 auto Outprojected = Map.project_out(isl::dim::out, first, n); 124 Result = Result.unite(Outprojected); 125 } 126 return Result; 127 } 128 129 /// Return the @p pos' range dimension, converted to an isl_union_pw_aff. 130 isl::union_pw_aff scheduleExtractDimAff(isl::union_map UMap, unsigned pos) { 131 auto SingleUMap = isl::union_map::empty(UMap.ctx()); 132 for (isl::map Map : UMap.get_map_list()) { 133 unsigned MapDims = unsignedFromIslSize(Map.range_tuple_dim()); 134 assert(MapDims > pos); 135 isl::map SingleMap = Map.project_out(isl::dim::out, 0, pos); 136 SingleMap = SingleMap.project_out(isl::dim::out, 1, MapDims - pos - 1); 137 SingleUMap = SingleUMap.unite(SingleMap); 138 }; 139 140 auto UAff = isl::union_pw_multi_aff(SingleUMap); 141 auto FirstMAff = isl::multi_union_pw_aff(UAff); 142 return FirstMAff.at(0); 143 } 144 145 /// Flatten a sequence-like first dimension. 146 /// 147 /// A sequence-like scatter dimension is constant, or at least only small 148 /// variation, typically the result of ordering a sequence of different 149 /// statements. An example would be: 150 /// { Stmt_A[] -> [0, X, ...]; Stmt_B[] -> [1, Y, ...] } 151 /// to schedule all instances of Stmt_A before any instance of Stmt_B. 152 /// 153 /// To flatten, first begin with an offset of zero. Then determine the lowest 154 /// possible value of the dimension, call it "i" [In the example we start at 0]. 155 /// Considering only schedules with that value, consider only instances with 156 /// that value and determine the extent of the next dimension. Let l_X(i) and 157 /// u_X(i) its minimum (lower bound) and maximum (upper bound) value. Add them 158 /// as "Offset + X - l_X(i)" to the new schedule, then add "u_X(i) - l_X(i) + 1" 159 /// to Offset and remove all i-instances from the old schedule. Repeat with the 160 /// remaining lowest value i' until there are no instances in the old schedule 161 /// left. 162 /// The example schedule would be transformed to: 163 /// { Stmt_X[] -> [X - l_X, ...]; Stmt_B -> [l_X - u_X + 1 + Y - l_Y, ...] } 164 isl::union_map tryFlattenSequence(isl::union_map Schedule) { 165 auto IslCtx = Schedule.ctx(); 166 auto ScatterSet = isl::set(Schedule.range()); 167 168 auto ParamSpace = Schedule.get_space().params(); 169 auto Dims = unsignedFromIslSize(ScatterSet.tuple_dim()); 170 assert(Dims >= 2u); 171 172 // Would cause an infinite loop. 173 if (!isDimBoundedByConstant(ScatterSet, 0)) { 174 LLVM_DEBUG(dbgs() << "Abort; dimension is not of fixed size\n"); 175 return {}; 176 } 177 178 auto AllDomains = Schedule.domain(); 179 auto AllDomainsToNull = isl::union_pw_multi_aff(AllDomains); 180 181 auto NewSchedule = isl::union_map::empty(ParamSpace.ctx()); 182 auto Counter = isl::pw_aff(isl::local_space(ParamSpace.set_from_params())); 183 184 while (!ScatterSet.is_empty()) { 185 LLVM_DEBUG(dbgs() << "Next counter:\n " << Counter << "\n"); 186 LLVM_DEBUG(dbgs() << "Remaining scatter set:\n " << ScatterSet << "\n"); 187 auto ThisSet = ScatterSet.project_out(isl::dim::set, 1, Dims - 1); 188 auto ThisFirst = ThisSet.lexmin(); 189 auto ScatterFirst = ThisFirst.add_dims(isl::dim::set, Dims - 1); 190 191 auto SubSchedule = Schedule.intersect_range(ScatterFirst); 192 SubSchedule = scheduleProjectOut(SubSchedule, 0, 1); 193 SubSchedule = flattenSchedule(SubSchedule); 194 195 unsigned SubDims = getNumScatterDims(SubSchedule); 196 assert(SubDims >= 1); 197 auto FirstSubSchedule = scheduleProjectOut(SubSchedule, 1, SubDims - 1); 198 auto FirstScheduleAff = scheduleExtractDimAff(FirstSubSchedule, 0); 199 auto RemainingSubSchedule = scheduleProjectOut(SubSchedule, 0, 1); 200 201 auto FirstSubScatter = isl::set(FirstSubSchedule.range()); 202 LLVM_DEBUG(dbgs() << "Next step in sequence is:\n " << FirstSubScatter 203 << "\n"); 204 205 if (!isDimBoundedByParameter(FirstSubScatter, 0)) { 206 LLVM_DEBUG(dbgs() << "Abort; sequence step is not bounded\n"); 207 return {}; 208 } 209 210 auto FirstSubScatterMap = isl::map::from_range(FirstSubScatter); 211 212 // isl_set_dim_max returns a strange isl_pw_aff with domain tuple_id of 213 // 'none'. It doesn't match with any space including a 0-dimensional 214 // anonymous tuple. 215 // Interesting, one can create such a set using 216 // isl_set_universe(ParamSpace). Bug? 217 auto PartMin = FirstSubScatterMap.dim_min(0); 218 auto PartMax = FirstSubScatterMap.dim_max(0); 219 auto One = isl::pw_aff(isl::set::universe(ParamSpace.set_from_params()), 220 isl::val::one(IslCtx)); 221 auto PartLen = PartMax.add(PartMin.neg()).add(One); 222 223 auto AllPartMin = isl::union_pw_aff(PartMin).pullback(AllDomainsToNull); 224 auto FirstScheduleAffNormalized = FirstScheduleAff.sub(AllPartMin); 225 auto AllCounter = isl::union_pw_aff(Counter).pullback(AllDomainsToNull); 226 auto FirstScheduleAffWithOffset = 227 FirstScheduleAffNormalized.add(AllCounter); 228 229 auto ScheduleWithOffset = 230 isl::union_map::from( 231 isl::union_pw_multi_aff(FirstScheduleAffWithOffset)) 232 .flat_range_product(RemainingSubSchedule); 233 NewSchedule = NewSchedule.unite(ScheduleWithOffset); 234 235 ScatterSet = ScatterSet.subtract(ScatterFirst); 236 Counter = Counter.add(PartLen); 237 } 238 239 LLVM_DEBUG(dbgs() << "Sequence-flatten result is:\n " << NewSchedule 240 << "\n"); 241 return NewSchedule; 242 } 243 244 /// Flatten a loop-like first dimension. 245 /// 246 /// A loop-like dimension is one that depends on a variable (usually a loop's 247 /// induction variable). Let the input schedule look like this: 248 /// { Stmt[i] -> [i, X, ...] } 249 /// 250 /// To flatten, we determine the largest extent of X which may not depend on the 251 /// actual value of i. Let l_X() the smallest possible value of X and u_X() its 252 /// largest value. Then, construct a new schedule 253 /// { Stmt[i] -> [i * (u_X() - l_X() + 1), ...] } 254 isl::union_map tryFlattenLoop(isl::union_map Schedule) { 255 assert(getNumScatterDims(Schedule) >= 2); 256 257 auto Remaining = scheduleProjectOut(Schedule, 0, 1); 258 auto SubSchedule = flattenSchedule(Remaining); 259 unsigned SubDims = getNumScatterDims(SubSchedule); 260 261 assert(SubDims >= 1); 262 263 auto SubExtent = isl::set(SubSchedule.range()); 264 auto SubExtentDims = unsignedFromIslSize(SubExtent.dim(isl::dim::param)); 265 SubExtent = SubExtent.project_out(isl::dim::param, 0, SubExtentDims); 266 SubExtent = SubExtent.project_out(isl::dim::set, 1, SubDims - 1); 267 268 if (!isDimBoundedByConstant(SubExtent, 0)) { 269 LLVM_DEBUG(dbgs() << "Abort; dimension not bounded by constant\n"); 270 return {}; 271 } 272 273 auto Min = SubExtent.dim_min(0); 274 LLVM_DEBUG(dbgs() << "Min bound:\n " << Min << "\n"); 275 auto MinVal = getConstant(Min, false, true); 276 auto Max = SubExtent.dim_max(0); 277 LLVM_DEBUG(dbgs() << "Max bound:\n " << Max << "\n"); 278 auto MaxVal = getConstant(Max, true, false); 279 280 if (MinVal.is_null() || MaxVal.is_null() || MinVal.is_nan() || 281 MaxVal.is_nan()) { 282 LLVM_DEBUG(dbgs() << "Abort; dimension bounds could not be determined\n"); 283 return {}; 284 } 285 286 auto FirstSubScheduleAff = scheduleExtractDimAff(SubSchedule, 0); 287 auto RemainingSubSchedule = scheduleProjectOut(std::move(SubSchedule), 0, 1); 288 289 auto LenVal = MaxVal.sub(MinVal).add(1); 290 auto FirstSubScheduleNormalized = subtract(FirstSubScheduleAff, MinVal); 291 292 // TODO: Normalize FirstAff to zero (convert to isl_map, determine minimum, 293 // subtract it) 294 auto FirstAff = scheduleExtractDimAff(Schedule, 0); 295 auto Offset = multiply(FirstAff, LenVal); 296 isl::union_pw_multi_aff Index = FirstSubScheduleNormalized.add(Offset); 297 auto IndexMap = isl::union_map::from(Index); 298 299 auto Result = IndexMap.flat_range_product(RemainingSubSchedule); 300 LLVM_DEBUG(dbgs() << "Loop-flatten result is:\n " << Result << "\n"); 301 return Result; 302 } 303 } // anonymous namespace 304 305 isl::union_map polly::flattenSchedule(isl::union_map Schedule) { 306 unsigned Dims = getNumScatterDims(Schedule); 307 LLVM_DEBUG(dbgs() << "Recursive schedule to process:\n " << Schedule 308 << "\n"); 309 310 // Base case; no dimensions left 311 if (Dims == 0) { 312 // TODO: Add one dimension? 313 return Schedule; 314 } 315 316 // Base case; already one-dimensional 317 if (Dims == 1) 318 return Schedule; 319 320 // Fixed dimension; no need to preserve variabledness. 321 if (!isVariableDim(Schedule)) { 322 LLVM_DEBUG(dbgs() << "Fixed dimension; try sequence flattening\n"); 323 auto NewScheduleSequence = tryFlattenSequence(Schedule); 324 if (!NewScheduleSequence.is_null()) 325 return NewScheduleSequence; 326 } 327 328 // Constant stride 329 LLVM_DEBUG(dbgs() << "Try loop flattening\n"); 330 auto NewScheduleLoop = tryFlattenLoop(Schedule); 331 if (!NewScheduleLoop.is_null()) 332 return NewScheduleLoop; 333 334 // Try again without loop condition (may blow up the number of pieces!!) 335 LLVM_DEBUG(dbgs() << "Try sequence flattening again\n"); 336 auto NewScheduleSequence = tryFlattenSequence(Schedule); 337 if (!NewScheduleSequence.is_null()) 338 return NewScheduleSequence; 339 340 // Cannot flatten 341 return Schedule; 342 } 343