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llvm/mlir/lib/Transforms/LoopUtils.cpp

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Introduce loop body skewing / loop pipelining / loop shifting utility. - loopBodySkew shifts statements of a loop body by stmt-wise delays, and is typically meant to be used to: - allow overlap of non-blocking start/wait until completion operations with other computation - allow shifting of statements (for better register reuse/locality/parallelism) - software pipelining (when applied to the innermost loop) - an additional argument specifies whether to unroll the prologue and epilogue. - add method to check SSA dominance preservation. - add a fake loop pipeline pass to test this utility. Sample input/output are below. While on this, fix/add following: - fix minor bug in getAddMulPureAffineExpr - add additional builder methods for common affine map cases - fix const_operand_iterator's for ForStmt, etc. When there is no such thing as 'const MLValue', the iterator shouldn't be returning const MLValue's. Returning MLValue is const correct. Sample input/output examples: 1) Simplest case: shift second statement by one. Input: for %i = 0 to 7 { %y = "foo"(%i) : (affineint) -> affineint %x = "bar"(%i) : (affineint) -> affineint } Output: #map0 = (d0) -> (d0 - 1) mlfunc @loop_nest_simple1() { %c8 = constant 8 : affineint %c0 = constant 0 : affineint %0 = "foo"(%c0) : (affineint) -> affineint for %i0 = 1 to 7 { %1 = "foo"(%i0) : (affineint) -> affineint %2 = affine_apply #map0(%i0) %3 = "bar"(%2) : (affineint) -> affineint } %4 = affine_apply #map0(%c8) %5 = "bar"(%4) : (affineint) -> affineint return } 2) DMA overlap: shift dma.wait and compute by one. Input for %i = 0 to 7 { %pingpong = affine_apply (d0) -> (d0 mod 2) (%i) "dma.enqueue"(%pingpong) : (affineint) -> affineint %pongping = affine_apply (d0) -> (d0 mod 2) (%i) "dma.wait"(%pongping) : (affineint) -> affineint "compute1"(%pongping) : (affineint) -> affineint } Output #map0 = (d0) -> (d0 mod 2) #map1 = (d0) -> (d0 - 1) #map2 = ()[s0] -> (s0 + 7) mlfunc @loop_nest_dma() { %c8 = constant 8 : affineint %c0 = constant 0 : affineint %0 = affine_apply #map0(%c0) %1 = "dma.enqueue"(%0) : (affineint) -> affineint for %i0 = 1 to 7 { %2 = affine_apply #map0(%i0) %3 = "dma.enqueue"(%2) : (affineint) -> affineint %4 = affine_apply #map1(%i0) %5 = affine_apply #map0(%4) %6 = "dma.wait"(%5) : (affineint) -> affineint %7 = "compute1"(%5) : (affineint) -> affineint } %8 = affine_apply #map1(%c8) %9 = affine_apply #map0(%8) %10 = "dma.wait"(%9) : (affineint) -> affineint %11 = "compute1"(%9) : (affineint) -> affineint return } 3) With arbitrary affine bound maps: Shift last two statements by two. Input: for %i = %N to ()[s0] -> (s0 + 7)()[%N] { %y = "foo"(%i) : (affineint) -> affineint %x = "bar"(%i) : (affineint) -> affineint %z = "foo_bar"(%i) : (affineint) -> (affineint) "bar_foo"(%i) : (affineint) -> (affineint) } Output #map0 = ()[s0] -> (s0 + 1) #map1 = ()[s0] -> (s0 + 2) #map2 = ()[s0] -> (s0 + 7) #map3 = (d0) -> (d0 - 2) #map4 = ()[s0] -> (s0 + 8) #map5 = ()[s0] -> (s0 + 9) for %i0 = %arg0 to #map0()[%arg0] { %0 = "foo"(%i0) : (affineint) -> affineint %1 = "bar"(%i0) : (affineint) -> affineint } for %i1 = #map1()[%arg0] to #map2()[%arg0] { %2 = "foo"(%i1) : (affineint) -> affineint %3 = "bar"(%i1) : (affineint) -> affineint %4 = affine_apply #map3(%i1) %5 = "foo_bar"(%4) : (affineint) -> affineint %6 = "bar_foo"(%4) : (affineint) -> affineint } for %i2 = #map4()[%arg0] to #map5()[%arg0] { %7 = affine_apply #map3(%i2) %8 = "foo_bar"(%7) : (affineint) -> affineint %9 = "bar_foo"(%7) : (affineint) -> affineint } 4) Shift one by zero, second by one, third by two for %i = 0 to 7 { %y = "foo"(%i) : (affineint) -> affineint %x = "bar"(%i) : (affineint) -> affineint %z = "foobar"(%i) : (affineint) -> affineint } #map0 = (d0) -> (d0 - 1) #map1 = (d0) -> (d0 - 2) #map2 = ()[s0] -> (s0 + 7) %c9 = constant 9 : affineint %c8 = constant 8 : affineint %c1 = constant 1 : affineint %c0 = constant 0 : affineint %0 = "foo"(%c0) : (affineint) -> affineint %1 = "foo"(%c1) : (affineint) -> affineint %2 = affine_apply #map0(%c1) %3 = "bar"(%2) : (affineint) -> affineint for %i0 = 2 to 7 { %4 = "foo"(%i0) : (affineint) -> affineint %5 = affine_apply #map0(%i0) %6 = "bar"(%5) : (affineint) -> affineint %7 = affine_apply #map1(%i0) %8 = "foobar"(%7) : (affineint) -> affineint } %9 = affine_apply #map0(%c8) %10 = "bar"(%9) : (affineint) -> affineint %11 = affine_apply #map1(%c8) %12 = "foobar"(%11) : (affineint) -> affineint %13 = affine_apply #map1(%c9) %14 = "foobar"(%13) : (affineint) -> affineint 5) SSA dominance violated; no shifting if a shift is specified for the second statement. for %i = 0 to 7 { %x = "foo"(%i) : (affineint) -> affineint "bar"(%x) : (affineint) -> affineint } PiperOrigin-RevId: 214975731
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//===- LoopUtils.cpp ---- Misc utilities for loop transformation ----------===//
//
// Copyright 2019 The MLIR Authors.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// =============================================================================
//
Introduce loop body skewing / loop pipelining / loop shifting utility. - loopBodySkew shifts statements of a loop body by stmt-wise delays, and is typically meant to be used to: - allow overlap of non-blocking start/wait until completion operations with other computation - allow shifting of statements (for better register reuse/locality/parallelism) - software pipelining (when applied to the innermost loop) - an additional argument specifies whether to unroll the prologue and epilogue. - add method to check SSA dominance preservation. - add a fake loop pipeline pass to test this utility. Sample input/output are below. While on this, fix/add following: - fix minor bug in getAddMulPureAffineExpr - add additional builder methods for common affine map cases - fix const_operand_iterator's for ForStmt, etc. When there is no such thing as 'const MLValue', the iterator shouldn't be returning const MLValue's. Returning MLValue is const correct. Sample input/output examples: 1) Simplest case: shift second statement by one. Input: for %i = 0 to 7 { %y = "foo"(%i) : (affineint) -> affineint %x = "bar"(%i) : (affineint) -> affineint } Output: #map0 = (d0) -> (d0 - 1) mlfunc @loop_nest_simple1() { %c8 = constant 8 : affineint %c0 = constant 0 : affineint %0 = "foo"(%c0) : (affineint) -> affineint for %i0 = 1 to 7 { %1 = "foo"(%i0) : (affineint) -> affineint %2 = affine_apply #map0(%i0) %3 = "bar"(%2) : (affineint) -> affineint } %4 = affine_apply #map0(%c8) %5 = "bar"(%4) : (affineint) -> affineint return } 2) DMA overlap: shift dma.wait and compute by one. Input for %i = 0 to 7 { %pingpong = affine_apply (d0) -> (d0 mod 2) (%i) "dma.enqueue"(%pingpong) : (affineint) -> affineint %pongping = affine_apply (d0) -> (d0 mod 2) (%i) "dma.wait"(%pongping) : (affineint) -> affineint "compute1"(%pongping) : (affineint) -> affineint } Output #map0 = (d0) -> (d0 mod 2) #map1 = (d0) -> (d0 - 1) #map2 = ()[s0] -> (s0 + 7) mlfunc @loop_nest_dma() { %c8 = constant 8 : affineint %c0 = constant 0 : affineint %0 = affine_apply #map0(%c0) %1 = "dma.enqueue"(%0) : (affineint) -> affineint for %i0 = 1 to 7 { %2 = affine_apply #map0(%i0) %3 = "dma.enqueue"(%2) : (affineint) -> affineint %4 = affine_apply #map1(%i0) %5 = affine_apply #map0(%4) %6 = "dma.wait"(%5) : (affineint) -> affineint %7 = "compute1"(%5) : (affineint) -> affineint } %8 = affine_apply #map1(%c8) %9 = affine_apply #map0(%8) %10 = "dma.wait"(%9) : (affineint) -> affineint %11 = "compute1"(%9) : (affineint) -> affineint return } 3) With arbitrary affine bound maps: Shift last two statements by two. Input: for %i = %N to ()[s0] -> (s0 + 7)()[%N] { %y = "foo"(%i) : (affineint) -> affineint %x = "bar"(%i) : (affineint) -> affineint %z = "foo_bar"(%i) : (affineint) -> (affineint) "bar_foo"(%i) : (affineint) -> (affineint) } Output #map0 = ()[s0] -> (s0 + 1) #map1 = ()[s0] -> (s0 + 2) #map2 = ()[s0] -> (s0 + 7) #map3 = (d0) -> (d0 - 2) #map4 = ()[s0] -> (s0 + 8) #map5 = ()[s0] -> (s0 + 9) for %i0 = %arg0 to #map0()[%arg0] { %0 = "foo"(%i0) : (affineint) -> affineint %1 = "bar"(%i0) : (affineint) -> affineint } for %i1 = #map1()[%arg0] to #map2()[%arg0] { %2 = "foo"(%i1) : (affineint) -> affineint %3 = "bar"(%i1) : (affineint) -> affineint %4 = affine_apply #map3(%i1) %5 = "foo_bar"(%4) : (affineint) -> affineint %6 = "bar_foo"(%4) : (affineint) -> affineint } for %i2 = #map4()[%arg0] to #map5()[%arg0] { %7 = affine_apply #map3(%i2) %8 = "foo_bar"(%7) : (affineint) -> affineint %9 = "bar_foo"(%7) : (affineint) -> affineint } 4) Shift one by zero, second by one, third by two for %i = 0 to 7 { %y = "foo"(%i) : (affineint) -> affineint %x = "bar"(%i) : (affineint) -> affineint %z = "foobar"(%i) : (affineint) -> affineint } #map0 = (d0) -> (d0 - 1) #map1 = (d0) -> (d0 - 2) #map2 = ()[s0] -> (s0 + 7) %c9 = constant 9 : affineint %c8 = constant 8 : affineint %c1 = constant 1 : affineint %c0 = constant 0 : affineint %0 = "foo"(%c0) : (affineint) -> affineint %1 = "foo"(%c1) : (affineint) -> affineint %2 = affine_apply #map0(%c1) %3 = "bar"(%2) : (affineint) -> affineint for %i0 = 2 to 7 { %4 = "foo"(%i0) : (affineint) -> affineint %5 = affine_apply #map0(%i0) %6 = "bar"(%5) : (affineint) -> affineint %7 = affine_apply #map1(%i0) %8 = "foobar"(%7) : (affineint) -> affineint } %9 = affine_apply #map0(%c8) %10 = "bar"(%9) : (affineint) -> affineint %11 = affine_apply #map1(%c8) %12 = "foobar"(%11) : (affineint) -> affineint %13 = affine_apply #map1(%c9) %14 = "foobar"(%13) : (affineint) -> affineint 5) SSA dominance violated; no shifting if a shift is specified for the second statement. for %i = 0 to 7 { %x = "foo"(%i) : (affineint) -> affineint "bar"(%x) : (affineint) -> affineint } PiperOrigin-RevId: 214975731
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// This file implements miscellaneous loop transformation routines.
//
//===----------------------------------------------------------------------===//
#include "mlir/Transforms/LoopUtils.h"
Extend getConstantTripCount to deal with a larger subset of loop bounds; make loop unroll/unroll-and-jam more powerful; add additional affine expr builder methods - use previously added analysis/simplification to infer multiple of unroll factor trip counts, making loop unroll/unroll-and-jam more general. - for loop unroll, support bounds that are single result affine map's with the same set of operands. For unknown loop bounds, loop unroll will now work as long as trip count can be determined to be a multiple of unroll factor. - extend getConstantTripCount to deal with single result affine map's with the same operands. move it to mlir/Analysis/LoopAnalysis.cpp - add additional builder utility methods for affine expr arithmetic (difference, mod/floordiv/ceildiv w.r.t postitive constant). simplify code to use the utility methods. - move affine analysis routines to AffineAnalysis.cpp/.h from AffineStructures.cpp/.h. - Rename LoopUnrollJam to LoopUnrollAndJam to match class name. - add an additional simplification for simplifyFloorDiv, simplifyCeilDiv - Rename AffineMap::getNumOperands() getNumInputs: an affine map by itself does not have operands. Operands are passed to it through affine_apply, from loop bounds/if condition's, etc., operands are stored in the latter. This should be sufficiently powerful for now as far as unroll/unroll-and-jam go for TPU code generation, and can move to other analyses/transformations. Loop nests like these are now unrolled without any cleanup loop being generated. for %i = 1 to 100 { // unroll factor 4: no cleanup loop will be generated. for %j = (d0) -> (d0) (%i) to (d0) -> (5*d0 + 3) (%i) { %x = "foo"(%j) : (affineint) -> i32 } } for %i = 1 to 100 { // unroll factor 4: no cleanup loop will be generated. for %j = (d0) -> (d0) (%i) to (d0) -> (d0 - d mod 4 - 1) (%i) { %y = "foo"(%j) : (affineint) -> i32 } } for %i = 1 to 100 { for %j = (d0) -> (d0) (%i) to (d0) -> (d0 + 128) (%i) { %x = "foo"() : () -> i32 } } TODO(bondhugula): extend this to LoopUnrollAndJam as well in the next CL (with minor changes). PiperOrigin-RevId: 212661212
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#include "mlir/Analysis/LoopAnalysis.h"
#include "mlir/IR/AffineExpr.h"
#include "mlir/IR/AffineMap.h"
#include "mlir/IR/Builders.h"
#include "mlir/IR/StandardOps.h"
#include "mlir/IR/Statements.h"
#include "mlir/IR/StmtVisitor.h"
Introduce loop body skewing / loop pipelining / loop shifting utility. - loopBodySkew shifts statements of a loop body by stmt-wise delays, and is typically meant to be used to: - allow overlap of non-blocking start/wait until completion operations with other computation - allow shifting of statements (for better register reuse/locality/parallelism) - software pipelining (when applied to the innermost loop) - an additional argument specifies whether to unroll the prologue and epilogue. - add method to check SSA dominance preservation. - add a fake loop pipeline pass to test this utility. Sample input/output are below. While on this, fix/add following: - fix minor bug in getAddMulPureAffineExpr - add additional builder methods for common affine map cases - fix const_operand_iterator's for ForStmt, etc. When there is no such thing as 'const MLValue', the iterator shouldn't be returning const MLValue's. Returning MLValue is const correct. Sample input/output examples: 1) Simplest case: shift second statement by one. Input: for %i = 0 to 7 { %y = "foo"(%i) : (affineint) -> affineint %x = "bar"(%i) : (affineint) -> affineint } Output: #map0 = (d0) -> (d0 - 1) mlfunc @loop_nest_simple1() { %c8 = constant 8 : affineint %c0 = constant 0 : affineint %0 = "foo"(%c0) : (affineint) -> affineint for %i0 = 1 to 7 { %1 = "foo"(%i0) : (affineint) -> affineint %2 = affine_apply #map0(%i0) %3 = "bar"(%2) : (affineint) -> affineint } %4 = affine_apply #map0(%c8) %5 = "bar"(%4) : (affineint) -> affineint return } 2) DMA overlap: shift dma.wait and compute by one. Input for %i = 0 to 7 { %pingpong = affine_apply (d0) -> (d0 mod 2) (%i) "dma.enqueue"(%pingpong) : (affineint) -> affineint %pongping = affine_apply (d0) -> (d0 mod 2) (%i) "dma.wait"(%pongping) : (affineint) -> affineint "compute1"(%pongping) : (affineint) -> affineint } Output #map0 = (d0) -> (d0 mod 2) #map1 = (d0) -> (d0 - 1) #map2 = ()[s0] -> (s0 + 7) mlfunc @loop_nest_dma() { %c8 = constant 8 : affineint %c0 = constant 0 : affineint %0 = affine_apply #map0(%c0) %1 = "dma.enqueue"(%0) : (affineint) -> affineint for %i0 = 1 to 7 { %2 = affine_apply #map0(%i0) %3 = "dma.enqueue"(%2) : (affineint) -> affineint %4 = affine_apply #map1(%i0) %5 = affine_apply #map0(%4) %6 = "dma.wait"(%5) : (affineint) -> affineint %7 = "compute1"(%5) : (affineint) -> affineint } %8 = affine_apply #map1(%c8) %9 = affine_apply #map0(%8) %10 = "dma.wait"(%9) : (affineint) -> affineint %11 = "compute1"(%9) : (affineint) -> affineint return } 3) With arbitrary affine bound maps: Shift last two statements by two. Input: for %i = %N to ()[s0] -> (s0 + 7)()[%N] { %y = "foo"(%i) : (affineint) -> affineint %x = "bar"(%i) : (affineint) -> affineint %z = "foo_bar"(%i) : (affineint) -> (affineint) "bar_foo"(%i) : (affineint) -> (affineint) } Output #map0 = ()[s0] -> (s0 + 1) #map1 = ()[s0] -> (s0 + 2) #map2 = ()[s0] -> (s0 + 7) #map3 = (d0) -> (d0 - 2) #map4 = ()[s0] -> (s0 + 8) #map5 = ()[s0] -> (s0 + 9) for %i0 = %arg0 to #map0()[%arg0] { %0 = "foo"(%i0) : (affineint) -> affineint %1 = "bar"(%i0) : (affineint) -> affineint } for %i1 = #map1()[%arg0] to #map2()[%arg0] { %2 = "foo"(%i1) : (affineint) -> affineint %3 = "bar"(%i1) : (affineint) -> affineint %4 = affine_apply #map3(%i1) %5 = "foo_bar"(%4) : (affineint) -> affineint %6 = "bar_foo"(%4) : (affineint) -> affineint } for %i2 = #map4()[%arg0] to #map5()[%arg0] { %7 = affine_apply #map3(%i2) %8 = "foo_bar"(%7) : (affineint) -> affineint %9 = "bar_foo"(%7) : (affineint) -> affineint } 4) Shift one by zero, second by one, third by two for %i = 0 to 7 { %y = "foo"(%i) : (affineint) -> affineint %x = "bar"(%i) : (affineint) -> affineint %z = "foobar"(%i) : (affineint) -> affineint } #map0 = (d0) -> (d0 - 1) #map1 = (d0) -> (d0 - 2) #map2 = ()[s0] -> (s0 + 7) %c9 = constant 9 : affineint %c8 = constant 8 : affineint %c1 = constant 1 : affineint %c0 = constant 0 : affineint %0 = "foo"(%c0) : (affineint) -> affineint %1 = "foo"(%c1) : (affineint) -> affineint %2 = affine_apply #map0(%c1) %3 = "bar"(%2) : (affineint) -> affineint for %i0 = 2 to 7 { %4 = "foo"(%i0) : (affineint) -> affineint %5 = affine_apply #map0(%i0) %6 = "bar"(%5) : (affineint) -> affineint %7 = affine_apply #map1(%i0) %8 = "foobar"(%7) : (affineint) -> affineint } %9 = affine_apply #map0(%c8) %10 = "bar"(%9) : (affineint) -> affineint %11 = affine_apply #map1(%c8) %12 = "foobar"(%11) : (affineint) -> affineint %13 = affine_apply #map1(%c9) %14 = "foobar"(%13) : (affineint) -> affineint 5) SSA dominance violated; no shifting if a shift is specified for the second statement. for %i = 0 to 7 { %x = "foo"(%i) : (affineint) -> affineint "bar"(%x) : (affineint) -> affineint } PiperOrigin-RevId: 214975731
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#include "llvm/ADT/DenseMap.h"
using namespace mlir;
/// Returns the upper bound of an unrolled loop with lower bound 'lb' and with
/// the specified trip count, stride, and unroll factor. Returns nullptr when
/// the trip count can't be expressed as an affine expression.
AffineMap mlir::getUnrolledLoopUpperBound(const ForStmt &forStmt,
unsigned unrollFactor,
MLFuncBuilder *builder) {
auto lbMap = forStmt.getLowerBoundMap();
// Single result lower bound map only.
if (lbMap.getNumResults() != 1)
return AffineMap::Invalid();
// Sometimes, the trip count cannot be expressed as an affine expression.
auto tripCount = getTripCountExpr(forStmt);
if (!tripCount)
return AffineMap::Invalid();
AffineExpr lb(lbMap.getResult(0));
unsigned step = forStmt.getStep();
auto newUb = lb + (tripCount - tripCount % unrollFactor - 1) * step;
return builder->getAffineMap(lbMap.getNumDims(), lbMap.getNumSymbols(),
{newUb}, {});
}
/// Returns the lower bound of the cleanup loop when unrolling a loop with lower
/// bound 'lb' and with the specified trip count, stride, and unroll factor.
/// Returns an AffinMap with nullptr storage (that evaluates to false)
/// when the trip count can't be expressed as an affine expression.
AffineMap mlir::getCleanupLoopLowerBound(const ForStmt &forStmt,
unsigned unrollFactor,
MLFuncBuilder *builder) {
auto lbMap = forStmt.getLowerBoundMap();
// Single result lower bound map only.
if (lbMap.getNumResults() != 1)
return AffineMap::Invalid();
// Sometimes the trip count cannot be expressed as an affine expression.
AffineExpr tripCount(getTripCountExpr(forStmt));
if (!tripCount)
return AffineMap::Invalid();
AffineExpr lb(lbMap.getResult(0));
unsigned step = forStmt.getStep();
auto newLb = lb + (tripCount - tripCount % unrollFactor) * step;
return builder->getAffineMap(lbMap.getNumDims(), lbMap.getNumSymbols(),
{newLb}, {});
}
/// Promotes the loop body of a forStmt to its containing block if the forStmt
/// was known to have a single iteration. Returns false otherwise.
Extend getConstantTripCount to deal with a larger subset of loop bounds; make loop unroll/unroll-and-jam more powerful; add additional affine expr builder methods - use previously added analysis/simplification to infer multiple of unroll factor trip counts, making loop unroll/unroll-and-jam more general. - for loop unroll, support bounds that are single result affine map's with the same set of operands. For unknown loop bounds, loop unroll will now work as long as trip count can be determined to be a multiple of unroll factor. - extend getConstantTripCount to deal with single result affine map's with the same operands. move it to mlir/Analysis/LoopAnalysis.cpp - add additional builder utility methods for affine expr arithmetic (difference, mod/floordiv/ceildiv w.r.t postitive constant). simplify code to use the utility methods. - move affine analysis routines to AffineAnalysis.cpp/.h from AffineStructures.cpp/.h. - Rename LoopUnrollJam to LoopUnrollAndJam to match class name. - add an additional simplification for simplifyFloorDiv, simplifyCeilDiv - Rename AffineMap::getNumOperands() getNumInputs: an affine map by itself does not have operands. Operands are passed to it through affine_apply, from loop bounds/if condition's, etc., operands are stored in the latter. This should be sufficiently powerful for now as far as unroll/unroll-and-jam go for TPU code generation, and can move to other analyses/transformations. Loop nests like these are now unrolled without any cleanup loop being generated. for %i = 1 to 100 { // unroll factor 4: no cleanup loop will be generated. for %j = (d0) -> (d0) (%i) to (d0) -> (5*d0 + 3) (%i) { %x = "foo"(%j) : (affineint) -> i32 } } for %i = 1 to 100 { // unroll factor 4: no cleanup loop will be generated. for %j = (d0) -> (d0) (%i) to (d0) -> (d0 - d mod 4 - 1) (%i) { %y = "foo"(%j) : (affineint) -> i32 } } for %i = 1 to 100 { for %j = (d0) -> (d0) (%i) to (d0) -> (d0 + 128) (%i) { %x = "foo"() : () -> i32 } } TODO(bondhugula): extend this to LoopUnrollAndJam as well in the next CL (with minor changes). PiperOrigin-RevId: 212661212
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// TODO(bondhugula): extend this for arbitrary affine bounds.
bool mlir::promoteIfSingleIteration(ForStmt *forStmt) {
Extend getConstantTripCount to deal with a larger subset of loop bounds; make loop unroll/unroll-and-jam more powerful; add additional affine expr builder methods - use previously added analysis/simplification to infer multiple of unroll factor trip counts, making loop unroll/unroll-and-jam more general. - for loop unroll, support bounds that are single result affine map's with the same set of operands. For unknown loop bounds, loop unroll will now work as long as trip count can be determined to be a multiple of unroll factor. - extend getConstantTripCount to deal with single result affine map's with the same operands. move it to mlir/Analysis/LoopAnalysis.cpp - add additional builder utility methods for affine expr arithmetic (difference, mod/floordiv/ceildiv w.r.t postitive constant). simplify code to use the utility methods. - move affine analysis routines to AffineAnalysis.cpp/.h from AffineStructures.cpp/.h. - Rename LoopUnrollJam to LoopUnrollAndJam to match class name. - add an additional simplification for simplifyFloorDiv, simplifyCeilDiv - Rename AffineMap::getNumOperands() getNumInputs: an affine map by itself does not have operands. Operands are passed to it through affine_apply, from loop bounds/if condition's, etc., operands are stored in the latter. This should be sufficiently powerful for now as far as unroll/unroll-and-jam go for TPU code generation, and can move to other analyses/transformations. Loop nests like these are now unrolled without any cleanup loop being generated. for %i = 1 to 100 { // unroll factor 4: no cleanup loop will be generated. for %j = (d0) -> (d0) (%i) to (d0) -> (5*d0 + 3) (%i) { %x = "foo"(%j) : (affineint) -> i32 } } for %i = 1 to 100 { // unroll factor 4: no cleanup loop will be generated. for %j = (d0) -> (d0) (%i) to (d0) -> (d0 - d mod 4 - 1) (%i) { %y = "foo"(%j) : (affineint) -> i32 } } for %i = 1 to 100 { for %j = (d0) -> (d0) (%i) to (d0) -> (d0 + 128) (%i) { %x = "foo"() : () -> i32 } } TODO(bondhugula): extend this to LoopUnrollAndJam as well in the next CL (with minor changes). PiperOrigin-RevId: 212661212
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Optional<uint64_t> tripCount = getConstantTripCount(*forStmt);
if (!tripCount.hasValue() || tripCount.getValue() != 1)
return false;
// TODO(mlir-team): there is no builder for a max.
if (forStmt->getLowerBoundMap().getNumResults() != 1)
return false;
// Replaces all IV uses to its single iteration value.
if (!forStmt->use_empty()) {
if (forStmt->hasConstantLowerBound()) {
auto *mlFunc = forStmt->findFunction();
MLFuncBuilder topBuilder(&mlFunc->front());
auto constOp = topBuilder.create<ConstantIndexOp>(
forStmt->getLoc(), forStmt->getConstantLowerBound());
forStmt->replaceAllUsesWith(constOp->getResult());
} else {
const AffineBound lb = forStmt->getLowerBound();
SmallVector<SSAValue *, 4> lbOperands(lb.operand_begin(),
lb.operand_end());
MLFuncBuilder builder(forStmt->getBlock(), StmtBlock::iterator(forStmt));
auto affineApplyOp = builder.create<AffineApplyOp>(
forStmt->getLoc(), lb.getMap(), lbOperands);
forStmt->replaceAllUsesWith(affineApplyOp->getResult(0));
}
}
// Move the loop body statements to the loop's containing block.
auto *block = forStmt->getBlock();
block->getStatements().splice(StmtBlock::iterator(forStmt),
forStmt->getStatements());
forStmt->eraseFromBlock();
return true;
}
/// Promotes all single iteration for stmt's in the MLFunction, i.e., moves
/// their body into the containing StmtBlock.
void mlir::promoteSingleIterationLoops(MLFunction *f) {
// Gathers all innermost loops through a post order pruned walk.
class LoopBodyPromoter : public StmtWalker<LoopBodyPromoter> {
public:
void visitForStmt(ForStmt *forStmt) { promoteIfSingleIteration(forStmt); }
};
LoopBodyPromoter fsw;
fsw.walkPostOrder(f);
}
Introduce loop body skewing / loop pipelining / loop shifting utility. - loopBodySkew shifts statements of a loop body by stmt-wise delays, and is typically meant to be used to: - allow overlap of non-blocking start/wait until completion operations with other computation - allow shifting of statements (for better register reuse/locality/parallelism) - software pipelining (when applied to the innermost loop) - an additional argument specifies whether to unroll the prologue and epilogue. - add method to check SSA dominance preservation. - add a fake loop pipeline pass to test this utility. Sample input/output are below. While on this, fix/add following: - fix minor bug in getAddMulPureAffineExpr - add additional builder methods for common affine map cases - fix const_operand_iterator's for ForStmt, etc. When there is no such thing as 'const MLValue', the iterator shouldn't be returning const MLValue's. Returning MLValue is const correct. Sample input/output examples: 1) Simplest case: shift second statement by one. Input: for %i = 0 to 7 { %y = "foo"(%i) : (affineint) -> affineint %x = "bar"(%i) : (affineint) -> affineint } Output: #map0 = (d0) -> (d0 - 1) mlfunc @loop_nest_simple1() { %c8 = constant 8 : affineint %c0 = constant 0 : affineint %0 = "foo"(%c0) : (affineint) -> affineint for %i0 = 1 to 7 { %1 = "foo"(%i0) : (affineint) -> affineint %2 = affine_apply #map0(%i0) %3 = "bar"(%2) : (affineint) -> affineint } %4 = affine_apply #map0(%c8) %5 = "bar"(%4) : (affineint) -> affineint return } 2) DMA overlap: shift dma.wait and compute by one. Input for %i = 0 to 7 { %pingpong = affine_apply (d0) -> (d0 mod 2) (%i) "dma.enqueue"(%pingpong) : (affineint) -> affineint %pongping = affine_apply (d0) -> (d0 mod 2) (%i) "dma.wait"(%pongping) : (affineint) -> affineint "compute1"(%pongping) : (affineint) -> affineint } Output #map0 = (d0) -> (d0 mod 2) #map1 = (d0) -> (d0 - 1) #map2 = ()[s0] -> (s0 + 7) mlfunc @loop_nest_dma() { %c8 = constant 8 : affineint %c0 = constant 0 : affineint %0 = affine_apply #map0(%c0) %1 = "dma.enqueue"(%0) : (affineint) -> affineint for %i0 = 1 to 7 { %2 = affine_apply #map0(%i0) %3 = "dma.enqueue"(%2) : (affineint) -> affineint %4 = affine_apply #map1(%i0) %5 = affine_apply #map0(%4) %6 = "dma.wait"(%5) : (affineint) -> affineint %7 = "compute1"(%5) : (affineint) -> affineint } %8 = affine_apply #map1(%c8) %9 = affine_apply #map0(%8) %10 = "dma.wait"(%9) : (affineint) -> affineint %11 = "compute1"(%9) : (affineint) -> affineint return } 3) With arbitrary affine bound maps: Shift last two statements by two. Input: for %i = %N to ()[s0] -> (s0 + 7)()[%N] { %y = "foo"(%i) : (affineint) -> affineint %x = "bar"(%i) : (affineint) -> affineint %z = "foo_bar"(%i) : (affineint) -> (affineint) "bar_foo"(%i) : (affineint) -> (affineint) } Output #map0 = ()[s0] -> (s0 + 1) #map1 = ()[s0] -> (s0 + 2) #map2 = ()[s0] -> (s0 + 7) #map3 = (d0) -> (d0 - 2) #map4 = ()[s0] -> (s0 + 8) #map5 = ()[s0] -> (s0 + 9) for %i0 = %arg0 to #map0()[%arg0] { %0 = "foo"(%i0) : (affineint) -> affineint %1 = "bar"(%i0) : (affineint) -> affineint } for %i1 = #map1()[%arg0] to #map2()[%arg0] { %2 = "foo"(%i1) : (affineint) -> affineint %3 = "bar"(%i1) : (affineint) -> affineint %4 = affine_apply #map3(%i1) %5 = "foo_bar"(%4) : (affineint) -> affineint %6 = "bar_foo"(%4) : (affineint) -> affineint } for %i2 = #map4()[%arg0] to #map5()[%arg0] { %7 = affine_apply #map3(%i2) %8 = "foo_bar"(%7) : (affineint) -> affineint %9 = "bar_foo"(%7) : (affineint) -> affineint } 4) Shift one by zero, second by one, third by two for %i = 0 to 7 { %y = "foo"(%i) : (affineint) -> affineint %x = "bar"(%i) : (affineint) -> affineint %z = "foobar"(%i) : (affineint) -> affineint } #map0 = (d0) -> (d0 - 1) #map1 = (d0) -> (d0 - 2) #map2 = ()[s0] -> (s0 + 7) %c9 = constant 9 : affineint %c8 = constant 8 : affineint %c1 = constant 1 : affineint %c0 = constant 0 : affineint %0 = "foo"(%c0) : (affineint) -> affineint %1 = "foo"(%c1) : (affineint) -> affineint %2 = affine_apply #map0(%c1) %3 = "bar"(%2) : (affineint) -> affineint for %i0 = 2 to 7 { %4 = "foo"(%i0) : (affineint) -> affineint %5 = affine_apply #map0(%i0) %6 = "bar"(%5) : (affineint) -> affineint %7 = affine_apply #map1(%i0) %8 = "foobar"(%7) : (affineint) -> affineint } %9 = affine_apply #map0(%c8) %10 = "bar"(%9) : (affineint) -> affineint %11 = affine_apply #map1(%c8) %12 = "foobar"(%11) : (affineint) -> affineint %13 = affine_apply #map1(%c9) %14 = "foobar"(%13) : (affineint) -> affineint 5) SSA dominance violated; no shifting if a shift is specified for the second statement. for %i = 0 to 7 { %x = "foo"(%i) : (affineint) -> affineint "bar"(%x) : (affineint) -> affineint } PiperOrigin-RevId: 214975731
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/// Generates a for 'stmt' with the specified lower and upper bounds while
/// generating the right IV remappings for the delayed statements. The
/// statement blocks that go into the loop are specified in stmtGroupQueue
/// starting from the specified offset, and in that order; the first element of
/// the pair specifies the delay applied to that group of statements. Returns
/// nullptr if the generated loop simplifies to a single iteration one.
static ForStmt *
generateLoop(AffineMap lb, AffineMap ub,
Introduce loop body skewing / loop pipelining / loop shifting utility. - loopBodySkew shifts statements of a loop body by stmt-wise delays, and is typically meant to be used to: - allow overlap of non-blocking start/wait until completion operations with other computation - allow shifting of statements (for better register reuse/locality/parallelism) - software pipelining (when applied to the innermost loop) - an additional argument specifies whether to unroll the prologue and epilogue. - add method to check SSA dominance preservation. - add a fake loop pipeline pass to test this utility. Sample input/output are below. While on this, fix/add following: - fix minor bug in getAddMulPureAffineExpr - add additional builder methods for common affine map cases - fix const_operand_iterator's for ForStmt, etc. When there is no such thing as 'const MLValue', the iterator shouldn't be returning const MLValue's. Returning MLValue is const correct. Sample input/output examples: 1) Simplest case: shift second statement by one. Input: for %i = 0 to 7 { %y = "foo"(%i) : (affineint) -> affineint %x = "bar"(%i) : (affineint) -> affineint } Output: #map0 = (d0) -> (d0 - 1) mlfunc @loop_nest_simple1() { %c8 = constant 8 : affineint %c0 = constant 0 : affineint %0 = "foo"(%c0) : (affineint) -> affineint for %i0 = 1 to 7 { %1 = "foo"(%i0) : (affineint) -> affineint %2 = affine_apply #map0(%i0) %3 = "bar"(%2) : (affineint) -> affineint } %4 = affine_apply #map0(%c8) %5 = "bar"(%4) : (affineint) -> affineint return } 2) DMA overlap: shift dma.wait and compute by one. Input for %i = 0 to 7 { %pingpong = affine_apply (d0) -> (d0 mod 2) (%i) "dma.enqueue"(%pingpong) : (affineint) -> affineint %pongping = affine_apply (d0) -> (d0 mod 2) (%i) "dma.wait"(%pongping) : (affineint) -> affineint "compute1"(%pongping) : (affineint) -> affineint } Output #map0 = (d0) -> (d0 mod 2) #map1 = (d0) -> (d0 - 1) #map2 = ()[s0] -> (s0 + 7) mlfunc @loop_nest_dma() { %c8 = constant 8 : affineint %c0 = constant 0 : affineint %0 = affine_apply #map0(%c0) %1 = "dma.enqueue"(%0) : (affineint) -> affineint for %i0 = 1 to 7 { %2 = affine_apply #map0(%i0) %3 = "dma.enqueue"(%2) : (affineint) -> affineint %4 = affine_apply #map1(%i0) %5 = affine_apply #map0(%4) %6 = "dma.wait"(%5) : (affineint) -> affineint %7 = "compute1"(%5) : (affineint) -> affineint } %8 = affine_apply #map1(%c8) %9 = affine_apply #map0(%8) %10 = "dma.wait"(%9) : (affineint) -> affineint %11 = "compute1"(%9) : (affineint) -> affineint return } 3) With arbitrary affine bound maps: Shift last two statements by two. Input: for %i = %N to ()[s0] -> (s0 + 7)()[%N] { %y = "foo"(%i) : (affineint) -> affineint %x = "bar"(%i) : (affineint) -> affineint %z = "foo_bar"(%i) : (affineint) -> (affineint) "bar_foo"(%i) : (affineint) -> (affineint) } Output #map0 = ()[s0] -> (s0 + 1) #map1 = ()[s0] -> (s0 + 2) #map2 = ()[s0] -> (s0 + 7) #map3 = (d0) -> (d0 - 2) #map4 = ()[s0] -> (s0 + 8) #map5 = ()[s0] -> (s0 + 9) for %i0 = %arg0 to #map0()[%arg0] { %0 = "foo"(%i0) : (affineint) -> affineint %1 = "bar"(%i0) : (affineint) -> affineint } for %i1 = #map1()[%arg0] to #map2()[%arg0] { %2 = "foo"(%i1) : (affineint) -> affineint %3 = "bar"(%i1) : (affineint) -> affineint %4 = affine_apply #map3(%i1) %5 = "foo_bar"(%4) : (affineint) -> affineint %6 = "bar_foo"(%4) : (affineint) -> affineint } for %i2 = #map4()[%arg0] to #map5()[%arg0] { %7 = affine_apply #map3(%i2) %8 = "foo_bar"(%7) : (affineint) -> affineint %9 = "bar_foo"(%7) : (affineint) -> affineint } 4) Shift one by zero, second by one, third by two for %i = 0 to 7 { %y = "foo"(%i) : (affineint) -> affineint %x = "bar"(%i) : (affineint) -> affineint %z = "foobar"(%i) : (affineint) -> affineint } #map0 = (d0) -> (d0 - 1) #map1 = (d0) -> (d0 - 2) #map2 = ()[s0] -> (s0 + 7) %c9 = constant 9 : affineint %c8 = constant 8 : affineint %c1 = constant 1 : affineint %c0 = constant 0 : affineint %0 = "foo"(%c0) : (affineint) -> affineint %1 = "foo"(%c1) : (affineint) -> affineint %2 = affine_apply #map0(%c1) %3 = "bar"(%2) : (affineint) -> affineint for %i0 = 2 to 7 { %4 = "foo"(%i0) : (affineint) -> affineint %5 = affine_apply #map0(%i0) %6 = "bar"(%5) : (affineint) -> affineint %7 = affine_apply #map1(%i0) %8 = "foobar"(%7) : (affineint) -> affineint } %9 = affine_apply #map0(%c8) %10 = "bar"(%9) : (affineint) -> affineint %11 = affine_apply #map1(%c8) %12 = "foobar"(%11) : (affineint) -> affineint %13 = affine_apply #map1(%c9) %14 = "foobar"(%13) : (affineint) -> affineint 5) SSA dominance violated; no shifting if a shift is specified for the second statement. for %i = 0 to 7 { %x = "foo"(%i) : (affineint) -> affineint "bar"(%x) : (affineint) -> affineint } PiperOrigin-RevId: 214975731
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const std::vector<std::pair<uint64_t, ArrayRef<Statement *>>>
&stmtGroupQueue,
unsigned offset, ForStmt *srcForStmt, MLFuncBuilder *b) {
SmallVector<MLValue *, 4> lbOperands(srcForStmt->getLowerBoundOperands());
SmallVector<MLValue *, 4> ubOperands(srcForStmt->getUpperBoundOperands());
auto *loopChunk =
b->createFor(srcForStmt->getLoc(), lbOperands, lb, ubOperands, ub);
OperationStmt::OperandMapTy operandMap;
for (auto it = stmtGroupQueue.begin() + offset, e = stmtGroupQueue.end();
it != e; ++it) {
auto elt = *it;
// All 'same delay' statements get added with the operands being remapped
// (to results of cloned statements).
// Generate the remapping if the delay is not zero: oldIV = newIV - delay.
// TODO(bondhugula): check if srcForStmt is actually used in elt.second
// instead of just checking if it's used at all.
if (!srcForStmt->use_empty() && elt.first != 0) {
auto b = MLFuncBuilder::getForStmtBodyBuilder(loopChunk);
auto *oldIV =
b.create<AffineApplyOp>(
srcForStmt->getLoc(),
b.getSingleDimShiftAffineMap(-static_cast<int64_t>(elt.first)),
loopChunk)
->getResult(0);
operandMap[srcForStmt] = cast<MLValue>(oldIV);
} else {
operandMap[srcForStmt] = static_cast<MLValue *>(loopChunk);
}
for (auto *stmt : elt.second) {
loopChunk->push_back(stmt->clone(operandMap, b->getContext()));
}
}
if (promoteIfSingleIteration(loopChunk))
return nullptr;
return loopChunk;
}
// Returns delay of that child statement of 'forStmt' which either has 'operand'
// as one of its operands or has a descendant statement with operand 'operand'.
// This is a naive implementation. If performance becomes an issue, a map can
// be used to store 'delays' - to look up the delay for a statement in constant
// time.
static uint64_t getContainingStmtDelay(const StmtOperand &operand,
const ForStmt &forStmt,
ArrayRef<uint64_t> delays) {
// Traverse up the statement hierarchy starting from the owner of operand to
// find the ancestor statement that resides in the block of 'forStmt'.
const Statement *stmt = operand.getOwner();
assert(stmt != nullptr);
while (stmt->getParentStmt() != &forStmt) {
stmt = stmt->getParentStmt();
assert(stmt && "traversing parent's should reach forStmt block");
}
// Look up the delay of 'stmt'.
unsigned j = 0;
for (const auto &s : forStmt) {
if (&s == stmt)
break;
j++;
}
assert(j < forStmt.getStatements().size() && "child stmt should be found");
return delays[j];
}
/// Checks if SSA dominance would be violated if a for stmt's body statements
/// are shifted by the specified delays. This method checks if a 'def' and all
/// its uses have the same delay factor.
bool mlir::checkDominancePreservationOnShift(const ForStmt &forStmt,
ArrayRef<uint64_t> delays) {
assert(delays.size() == forStmt.getStatements().size());
unsigned s = 0;
for (const auto &stmt : forStmt) {
// A for or if stmt does not produce any def/results (that are used
// outside).
if (auto *opStmt = dyn_cast<OperationStmt>(&stmt)) {
for (unsigned i = 0, e = opStmt->getNumResults(); i < e; ++i) {
const MLValue *result = opStmt->getResult(i);
for (const StmtOperand &use : result->getUses()) {
if (delays[s] != getContainingStmtDelay(use, forStmt, delays))
return false;
}
}
}
s++;
}
return true;
}
/// Skew the statements in the body of a 'for' statement with the specified
/// statement-wise delays. The delays are with respect to the original execution
/// order. A delay of zero for each statement will lead to no change.
// The skewing of statements with respect to one another can be used for example
// to allow overlap of asynchronous operations (such as DMA communication) with
// computation, or just relative shifting of statements for better register
// reuse, locality or parallelism. As such, the delays are typically expected to
// be at most of the order of the number of statements. This method should not
// be used as a substitute for loop distribution/fission.
// This method uses an algorithm// in time linear in the number of statements in
// the body of the for loop - (using the 'sweep line' paradigm). This method
// asserts preservation of SSA dominance. A check for that as well as that for
// memory-based depedence preservation check rests with the users of this
// method.
UtilResult mlir::stmtBodySkew(ForStmt *forStmt, ArrayRef<uint64_t> delays,
bool unrollPrologueEpilogue) {
if (forStmt->getStatements().empty())
return UtilResult::Success;
// If the trip counts aren't constant, we would need versioning and
// conditional guards (or context information to prevent such versioning). The
// better way to pipeline for such loops is to first tile them and extract
// constant trip count "full tiles" before applying this.
auto mayBeConstTripCount = getConstantTripCount(*forStmt);
if (!mayBeConstTripCount.hasValue())
return UtilResult::Failure;
uint64_t tripCount = mayBeConstTripCount.getValue();
assert(checkDominancePreservationOnShift(*forStmt, delays) &&
"dominance preservation failed\n");
unsigned numChildStmts = forStmt->getStatements().size();
// Do a linear time (counting) sort for the delays.
uint64_t maxDelay = 0;
for (unsigned i = 0; i < numChildStmts; i++) {
maxDelay = std::max(maxDelay, delays[i]);
}
// Such large delays are not the typical use case.
if (maxDelay >= numChildStmts)
return UtilResult::Failure;
// An array of statement groups sorted by delay amount; each group has all
// statements with the same delay in the order in which they appear in the
// body of the 'for' stmt.
std::vector<std::vector<Statement *>> sortedStmtGroups(maxDelay + 1);
unsigned pos = 0;
for (auto &stmt : *forStmt) {
auto delay = delays[pos++];
sortedStmtGroups[delay].push_back(&stmt);
}
// Unless the shifts have a specific pattern (which actually would be the
// common use case), prologue and epilogue are not meaningfully defined.
// Nevertheless, if 'unrollPrologueEpilogue' is set, we will treat the first
// loop generated as the prologue and the last as epilogue and unroll these
// fully.
ForStmt *prologue = nullptr;
ForStmt *epilogue = nullptr;
// Do a sweep over the sorted delays while storing open groups in a
// vector, and generating loop portions as necessary during the sweep. A block
// of statements is paired with its delay.
std::vector<std::pair<uint64_t, ArrayRef<Statement *>>> stmtGroupQueue;
auto origLbMap = forStmt->getLowerBoundMap();
Introduce loop body skewing / loop pipelining / loop shifting utility. - loopBodySkew shifts statements of a loop body by stmt-wise delays, and is typically meant to be used to: - allow overlap of non-blocking start/wait until completion operations with other computation - allow shifting of statements (for better register reuse/locality/parallelism) - software pipelining (when applied to the innermost loop) - an additional argument specifies whether to unroll the prologue and epilogue. - add method to check SSA dominance preservation. - add a fake loop pipeline pass to test this utility. Sample input/output are below. While on this, fix/add following: - fix minor bug in getAddMulPureAffineExpr - add additional builder methods for common affine map cases - fix const_operand_iterator's for ForStmt, etc. When there is no such thing as 'const MLValue', the iterator shouldn't be returning const MLValue's. Returning MLValue is const correct. Sample input/output examples: 1) Simplest case: shift second statement by one. Input: for %i = 0 to 7 { %y = "foo"(%i) : (affineint) -> affineint %x = "bar"(%i) : (affineint) -> affineint } Output: #map0 = (d0) -> (d0 - 1) mlfunc @loop_nest_simple1() { %c8 = constant 8 : affineint %c0 = constant 0 : affineint %0 = "foo"(%c0) : (affineint) -> affineint for %i0 = 1 to 7 { %1 = "foo"(%i0) : (affineint) -> affineint %2 = affine_apply #map0(%i0) %3 = "bar"(%2) : (affineint) -> affineint } %4 = affine_apply #map0(%c8) %5 = "bar"(%4) : (affineint) -> affineint return } 2) DMA overlap: shift dma.wait and compute by one. Input for %i = 0 to 7 { %pingpong = affine_apply (d0) -> (d0 mod 2) (%i) "dma.enqueue"(%pingpong) : (affineint) -> affineint %pongping = affine_apply (d0) -> (d0 mod 2) (%i) "dma.wait"(%pongping) : (affineint) -> affineint "compute1"(%pongping) : (affineint) -> affineint } Output #map0 = (d0) -> (d0 mod 2) #map1 = (d0) -> (d0 - 1) #map2 = ()[s0] -> (s0 + 7) mlfunc @loop_nest_dma() { %c8 = constant 8 : affineint %c0 = constant 0 : affineint %0 = affine_apply #map0(%c0) %1 = "dma.enqueue"(%0) : (affineint) -> affineint for %i0 = 1 to 7 { %2 = affine_apply #map0(%i0) %3 = "dma.enqueue"(%2) : (affineint) -> affineint %4 = affine_apply #map1(%i0) %5 = affine_apply #map0(%4) %6 = "dma.wait"(%5) : (affineint) -> affineint %7 = "compute1"(%5) : (affineint) -> affineint } %8 = affine_apply #map1(%c8) %9 = affine_apply #map0(%8) %10 = "dma.wait"(%9) : (affineint) -> affineint %11 = "compute1"(%9) : (affineint) -> affineint return } 3) With arbitrary affine bound maps: Shift last two statements by two. Input: for %i = %N to ()[s0] -> (s0 + 7)()[%N] { %y = "foo"(%i) : (affineint) -> affineint %x = "bar"(%i) : (affineint) -> affineint %z = "foo_bar"(%i) : (affineint) -> (affineint) "bar_foo"(%i) : (affineint) -> (affineint) } Output #map0 = ()[s0] -> (s0 + 1) #map1 = ()[s0] -> (s0 + 2) #map2 = ()[s0] -> (s0 + 7) #map3 = (d0) -> (d0 - 2) #map4 = ()[s0] -> (s0 + 8) #map5 = ()[s0] -> (s0 + 9) for %i0 = %arg0 to #map0()[%arg0] { %0 = "foo"(%i0) : (affineint) -> affineint %1 = "bar"(%i0) : (affineint) -> affineint } for %i1 = #map1()[%arg0] to #map2()[%arg0] { %2 = "foo"(%i1) : (affineint) -> affineint %3 = "bar"(%i1) : (affineint) -> affineint %4 = affine_apply #map3(%i1) %5 = "foo_bar"(%4) : (affineint) -> affineint %6 = "bar_foo"(%4) : (affineint) -> affineint } for %i2 = #map4()[%arg0] to #map5()[%arg0] { %7 = affine_apply #map3(%i2) %8 = "foo_bar"(%7) : (affineint) -> affineint %9 = "bar_foo"(%7) : (affineint) -> affineint } 4) Shift one by zero, second by one, third by two for %i = 0 to 7 { %y = "foo"(%i) : (affineint) -> affineint %x = "bar"(%i) : (affineint) -> affineint %z = "foobar"(%i) : (affineint) -> affineint } #map0 = (d0) -> (d0 - 1) #map1 = (d0) -> (d0 - 2) #map2 = ()[s0] -> (s0 + 7) %c9 = constant 9 : affineint %c8 = constant 8 : affineint %c1 = constant 1 : affineint %c0 = constant 0 : affineint %0 = "foo"(%c0) : (affineint) -> affineint %1 = "foo"(%c1) : (affineint) -> affineint %2 = affine_apply #map0(%c1) %3 = "bar"(%2) : (affineint) -> affineint for %i0 = 2 to 7 { %4 = "foo"(%i0) : (affineint) -> affineint %5 = affine_apply #map0(%i0) %6 = "bar"(%5) : (affineint) -> affineint %7 = affine_apply #map1(%i0) %8 = "foobar"(%7) : (affineint) -> affineint } %9 = affine_apply #map0(%c8) %10 = "bar"(%9) : (affineint) -> affineint %11 = affine_apply #map1(%c8) %12 = "foobar"(%11) : (affineint) -> affineint %13 = affine_apply #map1(%c9) %14 = "foobar"(%13) : (affineint) -> affineint 5) SSA dominance violated; no shifting if a shift is specified for the second statement. for %i = 0 to 7 { %x = "foo"(%i) : (affineint) -> affineint "bar"(%x) : (affineint) -> affineint } PiperOrigin-RevId: 214975731
2018-09-28 12:17:26 -07:00
uint64_t lbDelay = 0;
MLFuncBuilder b(forStmt);
for (uint64_t d = 0, e = sortedStmtGroups.size(); d < e; ++d) {
// If nothing is delayed by d, continue.
if (sortedStmtGroups[d].empty())
continue;
if (!stmtGroupQueue.empty()) {
assert(d >= 1 &&
"Queue expected to be empty when the first block is found");
// The interval for which the loop needs to be generated here is:
// ( lbDelay, min(lbDelay + tripCount - 1, d - 1) ] and the body of the
// loop needs to have all statements in stmtQueue in that order.
ForStmt *res;
if (lbDelay + tripCount - 1 < d - 1) {
res = generateLoop(
b.getShiftedAffineMap(origLbMap, lbDelay),
b.getShiftedAffineMap(origLbMap, lbDelay + tripCount - 1),
stmtGroupQueue, 0, forStmt, &b);
// Entire loop for the queued stmt groups generated, empty it.
stmtGroupQueue.clear();
lbDelay += tripCount;
} else {
res = generateLoop(b.getShiftedAffineMap(origLbMap, lbDelay),
b.getShiftedAffineMap(origLbMap, d - 1),
stmtGroupQueue, 0, forStmt, &b);
lbDelay = d;
}
if (!prologue && res)
prologue = res;
epilogue = res;
} else {
// Start of first interval.
lbDelay = d;
}
// Augment the list of statements that get into the current open interval.
stmtGroupQueue.push_back({d, sortedStmtGroups[d]});
}
// Those statements groups left in the queue now need to be processed (FIFO)
// and their loops completed.
for (unsigned i = 0, e = stmtGroupQueue.size(); i < e; ++i) {
uint64_t ubDelay = stmtGroupQueue[i].first + tripCount - 1;
epilogue = generateLoop(b.getShiftedAffineMap(origLbMap, lbDelay),
b.getShiftedAffineMap(origLbMap, ubDelay),
stmtGroupQueue, i, forStmt, &b);
lbDelay = ubDelay + 1;
if (!prologue)
prologue = epilogue;
}
// Erase the original for stmt.
forStmt->eraseFromBlock();
if (unrollPrologueEpilogue && prologue)
loopUnrollFull(prologue);
if (unrollPrologueEpilogue && !epilogue && epilogue != prologue)
loopUnrollFull(epilogue);
return UtilResult::Success;
}