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storage.cc
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storage.cc
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// Copyright 2020 Google LLC
//
// 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.
#include "storage.h"
#include "llvm/ADT/SmallString.h"
#include "loop_nest.h"
#include "sair_dialect.h"
#include "sequence.h"
namespace sair {
// Returns the layout of from_memref or to_memref operation value.
static MappingAttr FromToMemRefLayout(FromToMemRefOp op,
const IterationSpace &iter_space) {
int rank = op.getMemrefDomain().size();
int parallel_domain_size = op.getParallelDomain().size();
auto domain_to_layout = MappingAttr::GetIdentity(op.getContext(), rank)
.ShiftRight(parallel_domain_size);
return iter_space.mapping().Inverse().Compose(domain_to_layout);
}
Buffer::Buffer(mlir::Location loc, mlir::StringAttr name,
mlir::Type element_type, const LoopNest &loop_nest)
: MappedDomain(loc, "buffer", name, loop_nest),
element_type_(element_type) {
assert(element_type != nullptr);
}
Buffer::Buffer(FromToMemRefOp import_op, mlir::StringAttr name,
const LoopNest &loop_nest)
: Buffer(import_op.getLoc(), name, import_op.MemRefType().getElementType(),
loop_nest) {
import_op_ = import_op;
}
void Buffer::AddValue(ResultInstance value) {
values_.push_back(value);
if (auto defining_op = value.defining_op().dyn_cast<ComputeOpInstance>()) {
int position = value.result_number();
writes_.emplace_back(defining_op, position);
}
for (auto [user, pos] : value.GetUses()) {
auto compute_op_user = user.dyn_cast<ComputeOpInstance>();
if (compute_op_user == nullptr) continue;
// Position includes the domain. Shift the position to get ValueOperand
// position.
reads_.emplace_back(compute_op_user, pos - user.domain_size());
}
}
StorageAnalysis::StorageAnalysis(mlir::Operation *operation)
: StorageAnalysis(operation->getContext()) {
mlir::LogicalResult result = Init(cast<SairProgramOp>(operation));
assert(mlir::succeeded(result));
(void)result;
}
std::optional<StorageAnalysis> StorageAnalysis::Create(SairProgramOp program) {
StorageAnalysis analysis(program.getContext());
if (mlir::failed(analysis.Init(program))) {
return std::nullopt;
}
return analysis;
}
mlir::LogicalResult VerifyStorageAttrWellFormed(
mlir::Location loc, SairDialect *sair_dialect, mlir::TypeRange result_types,
llvm::DenseSet<mlir::Attribute> loop_names,
llvm::ArrayRef<mlir::Attribute> storage) {
if (storage.size() != result_types.size()) {
return mlir::emitError(loc) << "wrong number of storage entries";
}
llvm::DenseSet<mlir::Attribute> buffer_names;
for (auto [attr, type] : llvm::zip(storage, result_types)) {
if (attr.isa<UnitAttr>()) continue;
BufferAttr buffer = attr.dyn_cast<BufferAttr>();
if (buffer == nullptr) {
return mlir::emitError(loc)
<< "storage attribute must be an array of buffers "
"or unit attributes";
}
if (buffer.space() != sair_dialect->register_attr() &&
buffer.space() != sair_dialect->memory_attr()) {
return mlir::emitError(loc) << "invalid memory space " << buffer.space();
}
auto element_type = type.cast<ValueType>().ElementType();
if (buffer.space() == sair_dialect->memory_attr() &&
element_type.isa<mlir::IndexType, mlir::MemRefType>()) {
return mlir::emitError(loc)
<< "index and memref variables cannot be allocated in memory";
}
if ((buffer.space() == sair_dialect->memory_attr()) ^
buffer.name() != nullptr) {
return mlir::emitError(loc)
<< "buffers must have a name if and only if they "
"are stored in memory";
}
if (buffer.name() != nullptr &&
!buffer_names.insert(buffer.name()).second) {
return mlir::emitError(loc)
<< "operation cannot store two results in the same buffer";
}
if (buffer.layout() == nullptr) continue;
if (buffer.layout().mapping().HasUnknownExprs()) {
return mlir::emitError(loc) << "layouts cannot contain `?` expressions";
}
if (buffer.space() == sair_dialect->register_attr() &&
!buffer.layout().mapping().empty()) {
return mlir::emitError(loc)
<< "only 0D buffers can be stored in registers";
}
for (mlir::StringAttr loop_name : buffer.layout().names()) {
if (!loop_names.contains(loop_name)) {
return mlir::emitError(loc) << "unknown loop name " << loop_name;
}
}
}
return mlir::success();
}
// Returns the layout of `buffer` as a mapping from the iteration space of
// `op` to buffer dimensions.
static MappingAttr GetBufferLayout(
const OpInstance &op, BufferAttr buffer,
const IterationSpaceAnalysis &iteration_spaces) {
if (buffer.layout() == nullptr) return nullptr;
mlir::MLIRContext *context = op.context();
auto none_expr = MappingNoneExpr::get(context);
const IterationSpace &iter_space = iteration_spaces.Get(op);
MappingAttr mapping = buffer.layout().mapping();
llvm::SmallVector<MappingExpr> loops_to_indexed_loops_exprs(
mapping.UseDomainSize(), none_expr);
for (auto p : llvm::enumerate(buffer.layout().names())) {
auto it = llvm::find(iter_space.loop_names(), p.value());
assert(it != iter_space.loop_names().end());
int pos = std::distance(iter_space.loop_names().begin(), it);
loops_to_indexed_loops_exprs[p.index()] = MappingDimExpr::get(pos, context);
}
auto loops_to_indexed_loops = MappingAttr::get(
context, iter_space.mapping().size(), loops_to_indexed_loops_exprs);
return loops_to_indexed_loops.Compose(mapping);
}
// Unifies the shape of `buffer` with the shape specified by attribute
// `buffer_attr` of `op`. Raises an error if shapes cannot be unified.
static mlir::LogicalResult UnifyBufferShape(
mlir::StringAttr buffer_name, const OpInstance &op, MappingAttr layout,
const IterationSpace &op_iter_space,
const LoopFusionAnalysis &loop_analysis, Buffer &buffer) {
mlir::MLIRContext *context = op.context();
int iter_space_size = op_iter_space.mapping().size();
LoopNest op_loop_nest = loop_analysis.GetLoopNest(op_iter_space.loop_names());
MappingAttr loop_nest_mapping =
op_loop_nest.DomainToLoops().Resize(buffer.loop_nest().size());
// The operation loop nest might not cover all operation dimensions. We thus
// define a new domain that maps to loop nest dimensions when possible and
// directly to operation dimensions otherwise.
llvm::SmallVector<ValueAccessInstance> domain;
llvm::append_range(domain, op_loop_nest.getDomain());
auto none = MappingNoneExpr::get(context);
llvm::SmallVector<MappingExpr> constraints(op.domain_size(), none);
AssertSuccess(UnificationConstraints(
op_iter_space.mapping(), loop_nest_mapping.Resize(iter_space_size),
constraints));
DomainShapeAttr shape = op.GetShape();
for (int i = 0, e = op.domain_size(); i < e; ++i) {
if (!constraints[i].isa<MappingNoneExpr>()) continue;
auto renaming = MappingAttr::get(context, domain.size(), constraints);
auto mapping = shape.Dimension(i).dependency_mapping();
constraints[i] = MappingDimExpr::get(domain.size(), context);
domain.push_back({op.domain(i), renaming.Compose(mapping)});
}
auto renaming = MappingAttr::get(context, domain.size(), constraints);
auto domain_to_loops = loop_nest_mapping.ResizeUseDomain(domain.size());
auto domain_to_iter_space =
renaming.Compose(op_iter_space.mapping())
.Unify(domain_to_loops.Resize(iter_space_size));
auto domain_to_layout = domain_to_iter_space.Compose(layout).Canonicalize();
return buffer.UnifyMapping(op, domain_to_loops, domain_to_layout, domain);
}
// Trims `buffer` loop nest so that it can be accessed from the given iteration
// space, with the given layout. Layout is ignored if null.
static void TrimBufferLoopNestForAccess(
const IterationSpace &iter_space, MappingAttr layout,
const LoopFusionAnalysis &fusion_analysis, Buffer &buffer) {
// Trims the buffer loop nest so that only common loops that are not indexed
// by the layout remain.
int max_loop_nest = iter_space.NumCommonLoops(buffer.loop_nest());
if (layout != nullptr) {
llvm::SmallBitVector indexed_loops = layout.DependencyMask();
int first_indexed_loop = indexed_loops.find_first();
if (first_indexed_loop >= 0 && first_indexed_loop < max_loop_nest) {
max_loop_nest = first_indexed_loop;
}
}
LoopNest new_loop_nest = fusion_analysis.GetLoopNest(
iter_space.loop_names().take_front(max_loop_nest));
buffer.SetLoopNest(new_loop_nest);
}
// Declares buffer `attr` in `buffer_map`. If the
// buffer is already present, ensure that rank and element type are coherent and
// trims the buffer loop nest to the common prefix with `op` loop nest.
static mlir::LogicalResult DeclareBuffer(
const OpInstance &op, int result, BufferAttr attr,
const LoopFusionAnalysis &loop_analysis,
const IterationSpaceAnalysis &iteration_spaces,
llvm::DenseMap<mlir::Attribute, Buffer> &buffer_map,
llvm::DenseSet<mlir::Attribute> &buffers_with_rank_set) {
if (attr == nullptr || attr.name() == nullptr) return mlir::success();
mlir::Type element_type =
op.Result(result).GetType().cast<ValueType>().ElementType();
const IterationSpace &iter_space = iteration_spaces.Get(op);
const LoopNest &loop_nest =
loop_analysis.GetLoopNest(iter_space.loop_names());
auto it = buffer_map.try_emplace(attr.name(), op.getLoc(), attr.name(),
element_type, loop_nest);
Buffer &buffer = it.first->second;
// Check that element types match.
if (buffer.element_type() != element_type) {
mlir::InFlightDiagnostic diag =
op.EmitError()
<< "buffer " << attr.name()
<< " has different element type than in previous occurence";
diag.attachNote(buffer.location()) << "previous occurence here";
return mlir::failure();
}
MappingAttr layout = GetBufferLayout(op, attr, iteration_spaces);
TrimBufferLoopNestForAccess(iter_space, layout, loop_analysis, buffer);
if (layout == nullptr) return mlir::success();
// Ensure that the number of dimension is coherent.
if (!buffers_with_rank_set.insert(attr.name()).second) {
if (buffer.rank() != layout.size()) {
mlir::InFlightDiagnostic diag =
op.EmitError() << "buffer " << attr.name()
<< " rank differs from previous occurence";
diag.attachNote(buffer.location()) << "previous occurence here";
return mlir::failure();
}
} else {
buffer.AddNonePrefixToMapping(layout.size());
}
return UnifyBufferShape(attr.name(), op, layout, iter_space, loop_analysis,
buffer);
}
// Declare buffers used by `program` in `buffers`. If a buffer has multiple
// uses, chek that element type and rank are compatible.
static mlir::LogicalResult DeclareBuffers(
SairProgramOp program, const IterationSpaceAnalysis &iteration_spaces,
const LoopFusionAnalysis &fusion_analysis,
llvm::DenseMap<mlir::Attribute, Buffer> &buffers) {
llvm::DenseSet<mlir::Attribute> buffers_with_rank_set;
// Declare external buffers imported using from/to memref.
mlir::WalkResult result =
program.walk([&](FromToMemRefOp op) -> mlir::WalkResult {
auto sair_op = cast<SairOp>(op.getOperation());
OpInstance op_instance(sair_op);
auto name = mlir::StringAttr::get(op.getContext(), op.getBufferName());
const IterationSpace &iter_space = iteration_spaces.Get(op_instance);
const LoopNest &loop_nest =
fusion_analysis.GetLoopNest(iter_space.loop_names());
auto [buffer_it, was_inserted] =
buffers.try_emplace(name, op, name, loop_nest);
if (!was_inserted)
return op.emitError() << "buffer name is already used";
MappingAttr layout = FromToMemRefLayout(op, iter_space);
buffers_with_rank_set.insert(name);
buffer_it->second.AddNonePrefixToMapping(layout.size());
return UnifyBufferShape(name, op_instance, layout, iter_space,
fusion_analysis, buffer_it->second);
});
if (result.wasInterrupted()) return mlir::failure();
// Declare internal buffers.
result = program.TryWalkComputeOpInstances(
[&](const ComputeOpInstance &op) -> mlir::WalkResult {
for (int i = 0, e = op.num_results(); i < e; ++i) {
BufferAttr buffer_attr = op.Storage(i);
if (mlir::failed(DeclareBuffer(op, i, buffer_attr, fusion_analysis,
iteration_spaces, buffers,
buffers_with_rank_set))) {
return mlir::failure();
}
}
return mlir::success();
});
if (result.wasInterrupted()) return mlir::failure();
// Ensure all buffers layout is fully specified.
for (auto [name, buffer] : buffers) {
if (buffer.mapping().HasNoneExprs()) {
return buffer.EmitError() << "layout is not fully specified";
}
}
return mlir::failure(result.wasInterrupted());
}
// Computes how values are stored and stores the result into `value_storages`.
mlir::LogicalResult StorageAnalysis::ComputeValueStorages(
SairProgramOp program, const LoopFusionAnalysis &fusion_analysis,
const IterationSpaceAnalysis &iteration_spaces) {
mlir::MLIRContext *context = program.getContext();
auto *sair_dialect = static_cast<SairDialect *>(program->getDialect());
mlir::StringAttr memory_space = sair_dialect->memory_attr();
// Initialize storage information from compute operations.
auto result = program.TryWalkComputeOpInstances(
[&](const ComputeOpInstance &op) -> mlir::WalkResult {
for (int i = 0, e = op.num_results(); i < e; ++i) {
BufferAttr buffer = op.Storage(i);
if (buffer == nullptr) continue;
MappingAttr layout = GetBufferLayout(op, buffer, iteration_spaces);
ValueStorage storage(buffer.space(), buffer.name(), layout);
if (mlir::failed(SetStorage(op.Result(i), storage, fusion_analysis,
iteration_spaces))) {
return mlir::failure();
}
}
return mlir::success();
});
if (result.wasInterrupted()) return mlir::failure();
// Initialize from from_memref operations.
result = program.walk([&](SairFromMemRefOp op) -> mlir::WalkResult {
OpInstance op_instance(cast<SairOp>(op.getOperation()));
const IterationSpace &iter_space = iteration_spaces.Get(op_instance);
MappingAttr layout = iter_space.mapping().Inverse().Compose(op.Layout());
ValueStorage storage(memory_space, op.getBufferNameAttr(), layout);
return SetStorage(op_instance.Result(0), storage, fusion_analysis,
iteration_spaces);
});
if (result.wasInterrupted()) return mlir::failure();
// Initialize from from_scalar operations.
result = program.walk([&](SairFromScalarOp op) -> mlir::WalkResult {
auto layout = MappingAttr::get(context, 0, {});
ValueStorage storage(sair_dialect->register_attr(), nullptr, layout);
OpInstance op_instance(cast<SairOp>(op.getOperation()));
return SetStorage(op_instance.Result(0), storage, fusion_analysis,
iteration_spaces);
});
if (result.wasInterrupted()) return mlir::failure();
// Initialize from to_memref operations.
result = program.walk([&](SairToMemRefOp op) -> mlir::WalkResult {
OpInstance op_instance(cast<SairOp>(op.getOperation()));
const IterationSpace &iter_space = iteration_spaces.Get(op_instance);
MappingAttr layout = iter_space.mapping().Inverse().Compose(op.Layout());
ValueStorage operand_storage(memory_space, op.getBufferNameAttr(), layout);
auto value = OperandInstance(op.Value(), op_instance).GetValue();
if (!value.has_value()) return mlir::success();
ValueStorage storage =
operand_storage.Map(op_instance, value->defining_op(),
op.Value().Mapping().Inverse(), iteration_spaces);
return SetStorage(*value, storage, fusion_analysis, iteration_spaces);
});
if (result.wasInterrupted()) return mlir::failure();
// Ensure all sair values have an entry.
program.WalkOpInstances([&](const OpInstance &op) {
for (ResultInstance result : op.Results()) {
value_storages_.FindAndConstruct(result);
}
});
return mlir::success();
}
mlir::LogicalResult StorageAnalysis::Init(SairProgramOp program) {
// TODO(b/181938550): use cached analysis.
SequenceAnalysis sequence_analysis(program);
LoopFusionAnalysis fusion_analysis(program, &sequence_analysis);
IterationSpaceAnalysis iteration_spaces(program);
if (mlir::failed(DeclareBuffers(program, iteration_spaces, fusion_analysis,
buffers_))) {
return mlir::failure();
}
if (mlir::failed(
ComputeValueStorages(program, fusion_analysis, iteration_spaces))) {
return mlir::failure();
}
if (mlir::failed(VerifyAndMinimizeBufferLoopNests(
fusion_analysis, iteration_spaces, sequence_analysis))) {
return mlir::failure();
}
// Ensure that writes to external buffers occure after the buffer is defined.
for (auto &[name, buffer] : buffers_) {
if (!buffer.is_external()) continue;
OperandInstance memref(
buffer.import_op().MemRef(),
OpInstance(cast<SairOp>(buffer.import_op().getOperation())));
auto memref_value = memref.GetValue();
if (!memref_value.has_value()) continue;
OpInstance defining_op = memref_value->defining_op();
// We only need to check writes as reads always occure after writes.
for (auto write : buffer.writes()) {
if (sequence_analysis.IsBefore(write.first, defining_op)) {
mlir::InFlightDiagnostic diag = write.first.EmitError()
<< "buffer " << name
<< " used before it is defined";
defining_op.AttachNote(diag) << "buffer defined here";
return mlir::failure();
}
}
}
return mlir::success();
}
void StorageAnalysis::MergeStorage(
ResultInstance value, const ValueStorage &new_storage,
const LoopFusionAnalysis &fusion_analysis,
const IterationSpaceAnalysis &iteration_spaces) {
AssertSuccess(
SetStorage(value, new_storage, fusion_analysis, iteration_spaces));
}
mlir::StringAttr StorageAnalysis::GetFreshBufferName() {
llvm::SmallString<10> name("buffer_");
int original_size = name.size();
mlir::StringAttr attr;
do {
name.resize(original_size);
name += std::to_string(next_buffer_id_++);
attr = mlir::StringAttr::get(context_, name);
} while (buffers_.count(attr) > 0);
return attr;
}
void StorageAnalysis::AddDimensionsToBuffer(
mlir::StringAttr buffer_name, const OpInstance &op,
const IterationSpace &op_iter_space,
const LoopFusionAnalysis &fusion_analysis, MappingAttr new_layout) {
Buffer &buffer = buffers_.find(buffer_name)->second;
assert(new_layout != nullptr);
assert(new_layout.size() >= buffer.mapping().size());
assert(!buffer.is_external());
// Extend buffer domain.
TrimBufferLoopNestForAccess(op_iter_space, new_layout, fusion_analysis,
buffer);
int old_size = buffer.rank();
buffer.AddNonePrefixToMapping(new_layout.size() - old_size);
AssertSuccess(UnifyBufferShape(buffer_name, op, new_layout, op_iter_space,
fusion_analysis, buffer));
// Add a dimension to values layout.
for (ResultInstance value : buffer.values()) {
ValueStorage &storage = value_storages_.find(value)->second;
storage.AddUnknownPrefixToLayout(new_layout.size() - old_size);
}
}
// Update the storage information for value. Updates buffers to register new
// buffer uses.
static mlir::LogicalResult UpdateStorage(
ResultInstance value, const ValueStorage &new_storage,
const LoopFusionAnalysis &fusion_analysis,
const IterationSpaceAnalysis &iteration_spaces, ValueStorage &storage,
llvm::DenseMap<mlir::Attribute, Buffer> &buffers) {
if (storage.buffer_name() == nullptr &&
new_storage.buffer_name() != nullptr) {
Buffer &buffer = buffers.find(new_storage.buffer_name())->second;
buffer.AddValue(value);
// Trim buffer loop nest to ensure it can be used from value def and uses
// iteration spaces.
OpInstance defining_op = value.defining_op();
TrimBufferLoopNestForAccess(iteration_spaces.Get(defining_op), nullptr,
fusion_analysis, buffer);
for (auto &[user, pos] : value.GetUses()) {
(void)pos;
TrimBufferLoopNestForAccess(iteration_spaces.Get(user), nullptr,
fusion_analysis, buffer);
}
}
if (mlir::failed(storage.MergeSpace(new_storage.space()))) {
return value.defining_op().EmitError()
<< "conflicting memory spaces: expected " << new_storage.space()
<< ", got " << storage.space();
}
if (mlir::failed(storage.MergeBufferName(new_storage.buffer_name()))) {
return value.defining_op().EmitError()
<< "conflicting buffer names: expected " << new_storage.buffer_name()
<< ", got " << storage.buffer_name();
}
MappingAttr canonical_layout;
if (new_storage.layout() != nullptr) {
canonical_layout = new_storage.layout().Canonicalize();
}
if (mlir::failed(storage.MergeLayout(canonical_layout))) {
return value.defining_op().EmitError()
<< "conflicting layouts: expected " << canonical_layout << ", got "
<< storage.layout();
}
return mlir::success();
}
mlir::LogicalResult StorageAnalysis::SetStorage(
ResultInstance value, ValueStorage storage,
const LoopFusionAnalysis &fusion_analysis,
const IterationSpaceAnalysis &iteration_spaces) {
llvm::SmallVector<ResultInstance> work_list;
// Merge storage information for a value with existing information. Fails and
// emits an error in case of conflicts.
auto update_storage = [&](ResultInstance value,
ValueStorage new_storage) -> mlir::LogicalResult {
ValueStorage &storage = value_storages_[value];
if (new_storage == storage) return mlir::success();
work_list.push_back(value);
return UpdateStorage(value, new_storage, fusion_analysis, iteration_spaces,
storage, buffers_);
};
if (mlir::failed(update_storage(value, storage))) return mlir::failure();
// Propagate storage information.
while (!work_list.empty()) {
ResultInstance value = work_list.pop_back_val();
ValueStorage storage = value_storages_[value];
// Forward propagation.
for (auto &[user, use_pos] : value.GetUses()) {
if (user.is_copy()) continue;
mlir::Operation *sair_op = user.GetDuplicatedOp();
// Get the position relative the SairValue operands.
int operand_pos = use_pos - user.domain_size();
int result;
if (isa<SairProjAnyOp, SairProjLastOp, SairFbyOp>(sair_op)) {
result = 0;
} else if (auto map_reduce = dyn_cast<SairMapReduceOp>(sair_op)) {
if (use_pos >= map_reduce.Inits().size()) continue;
result = operand_pos;
} else {
continue;
}
ValueStorage new_storage =
*storage.Map(user.Operand(operand_pos), iteration_spaces);
if (mlir::failed(update_storage(user.Result(result), new_storage))) {
return mlir::failure();
}
}
// Backward propagation.
OpInstance defining_op = value.defining_op();
if (defining_op.is_copy()) continue;
mlir::Operation *mlir_def_op = defining_op.GetDuplicatedOp();
// Handle map-reduce separately.
if (auto map_reduce = dyn_cast<SairMapReduceOp>(mlir_def_op)) {
int pos = value.result_number();
OperandInstance operand(map_reduce.Inits()[pos], defining_op);
auto operand_value = operand.GetValue();
if (!operand_value.has_value()) continue;
ValueStorage new_storage =
storage.Map(defining_op, operand_value->defining_op(),
operand.Mapping().Inverse(), iteration_spaces);
if (mlir::failed(update_storage(*operand_value, new_storage))) {
return mlir::failure();
}
continue;
}
if (!isa<SairProjAnyOp, SairProjLastOp, SairFbyOp>(mlir_def_op)) continue;
for (OperandInstance operand : defining_op.Operands()) {
auto value = operand.GetValue();
if (!value.has_value()) continue;
ValueStorage new_storage =
storage.Map(defining_op, value->defining_op(),
operand.Mapping().Inverse(), iteration_spaces);
if (mlir::failed(update_storage(*value, new_storage))) {
return mlir::failure();
}
}
}
return mlir::success();
}
// Ensures that we can insert a malloc operation for the buffer. Increases
// `min_num_loops` to make sure that a malloc operation can be inserted if
// needed.
static mlir::LogicalResult CheckMallocInsertionPoint(
mlir::StringAttr buffer_name, const Buffer &buffer,
const llvm::SmallBitVector &used_dimensions,
const IterationSpaceAnalysis &iteration_spaces,
const SequenceAnalysis &sequence_analysis, int &min_num_loops) {
// Find the first compute op writting to the buffer.
ComputeOpInstance first_write = buffer.writes().front().first;
for (auto p : buffer.writes()) {
if (sequence_analysis.IsBefore(p.first, first_write)) {
first_write = p.first;
}
}
llvm::ArrayRef<mlir::StringAttr> write_loops =
iteration_spaces.Get(first_write).loop_names();
for (int dim : used_dimensions.set_bits()) {
OpInstance dimension_op = buffer.getDomain()[dim].value.defining_op();
if (sequence_analysis.IsBefore(first_write, dimension_op)) {
mlir::InFlightDiagnostic diag =
first_write.EmitError()
<< "buffer " << buffer_name
<< " is used before one of its dimensions is defined";
dimension_op.AttachNote(diag) << "dimension defined here";
return mlir::failure();
}
for (OperandInstance operand : dimension_op.Operands()) {
auto value = operand.GetValue();
if (!value.has_value()) continue;
OpInstance defining_op = value->defining_op();
llvm::ArrayRef<mlir::StringAttr> operand_loops =
iteration_spaces.Get(defining_op).loop_names();
int new_min = std::min(write_loops.size(), operand_loops.size());
for (; new_min > 0; --new_min) {
if (operand_loops[new_min - 1] == write_loops[new_min - 1]) break;
}
if (new_min > buffer.loop_nest().size()) {
mlir::InFlightDiagnostic diag =
first_write.EmitError()
<< "buffer " << buffer_name
<< " depends on a dimension that is defined after the buffer "
"is allocated";
dimension_op.AttachNote(diag) << "dimension defined here";
return mlir::failure();
}
min_num_loops = std::max(min_num_loops, new_min);
}
}
return mlir::success();
}
mlir::LogicalResult StorageAnalysis::VerifyAndMinimizeBufferLoopNests(
const LoopFusionAnalysis &fusion_analysis,
const IterationSpaceAnalysis &iteration_spaces,
const SequenceAnalysis &sequence_analysis) {
for (auto &[name_attr, buffer] : buffers_) {
mlir::StringAttr name = name_attr.cast<mlir::StringAttr>();
MappingAttr mapping = buffer.NestedMapping();
DomainShapeAttr domain_shape = buffer.DomainShape();
if (mlir::failed(VerifyMappingShape(buffer, mapping, domain_shape))) {
return mlir::failure();
}
DomainShapeAttr shape = domain_shape.AccessedShape(mapping);
int rank = shape.NumDimensions();
int min_num_loops = 0;
for (int i = buffer.loop_nest().size(); i < rank; ++i) {
int max_dependency =
shape.Dimension(i).dependency_mapping().MinDomainSize();
min_num_loops = std::max(min_num_loops, max_dependency);
}
if (min_num_loops > buffer.loop_nest().size()) {
return buffer.EmitError()
<< "layout depends on loops it cannot be nested in";
}
// We cannot minimize external buffers loop nests.
if (buffer.is_external()) continue;
llvm::SmallBitVector used_dimensions = buffer.mapping().DependencyMask();
if (mlir::failed(CheckMallocInsertionPoint(
name, buffer, used_dimensions, iteration_spaces, sequence_analysis,
min_num_loops))) {
return mlir::failure();
}
// Minimize layout loop-nest.
LoopNest new_loop_nest = fusion_analysis.GetLoopNest(
buffer.loop_nest().take_front(min_num_loops));
buffer.SetLoopNest(new_loop_nest);
}
return mlir::success();
}
void StorageAnalysis::CreateBuffer(
ResultInstance value, llvm::ArrayRef<mlir::StringAttr> loop_names,
const LoopFusionAnalysis &fusion_analysis,
const IterationSpaceAnalysis &iteration_spaces) {
mlir::StringAttr buffer_name = GetFreshBufferName();
mlir::Type element_type = value.GetType().cast<ValueType>().ElementType();
LoopNest loop_nest = fusion_analysis.GetLoopNest(loop_names);
buffers_.try_emplace(buffer_name, value.defining_op().getLoc(), buffer_name,
element_type, loop_nest);
auto *sair_dialect = value.defining_op().GetSairDialect();
ValueStorage storage = GetStorage(value);
AssertSuccess(storage.MergeBufferName(buffer_name));
AssertSuccess(storage.MergeSpace(sair_dialect->memory_attr()));
MergeStorage(value, storage, fusion_analysis, iteration_spaces);
}
// Ensures that communication between the producer and the user of operand only
// occurs within the same loop iteration or along dimensions that are
// materialized in memory.
static mlir::LogicalResult VerifyCommunicationVolume(
const OpInstance &op, const IterationSpace &use_iter_space,
const ValueAccessInstance &operand,
const IterationSpaceAnalysis &iteration_spaces,
const StorageAnalysis &storage_analysis) {
const IterationSpace &def_iter_space =
iteration_spaces.Get(operand.value.defining_op());
// Only check if loop nest are specified.
if (!use_iter_space.fully_specified() || !def_iter_space.fully_specified()) {
return mlir::success();
}
const ValueStorage &storage = storage_analysis.GetStorage(operand.value);
// Success if storage is not yet specified.
if (storage.layout() == nullptr) return mlir::success();
MappingAttr communication_volume = CommunicationVolume(
operand.mapping.size(), def_iter_space, use_iter_space);
MappingAttr layout_to_operand =
def_iter_space.mapping().Compose(storage.layout()).Inverse();
MappingAttr layout_to_communication_volume =
layout_to_operand.Compose(communication_volume).Canonicalize();
// Check that the layout covers the sub-domain of the operand that is not
// covered by common dimensions.
if (layout_to_communication_volume.HasNoneExprs()) {
mlir::InFlightDiagnostic diag =
op.EmitError()
<< "operand storage must cover all operand dimensions "
"that are not covered by loops common to both operand and user";
operand.value.defining_op().AttachNote(diag) << "operand defined here";
return mlir::failure();
}
return mlir::success();
}
// Verifies that `buffer` is not written to by operations other that
// `allowed_write` between `from` and `to`. `allowed_write` may be null in the
// case were no write is allowed between `from` and `to`.
//
// If `from` is in loop nest [A, B] and `to` is in loop nest [A, C] where A, B
// and C are lists of loops with loops of B and C distinct, we consider that
// there is a write between `from` and `to` if any of the following condition is
// statisfied:
// * If there is a write operation between `from` and `to` operations.
// * If there is a write operation before `from` that is nested in at least one
// loop of B and whose layout differs from `layout`. This corresponds to the
// case where the value is produced in a loop nest and is overwritten in the
// same loop nest.
// * If there is a write operation after `to` that is nested in at least one
// loop of C. This corresponds to the case where the value is overwritten in
// the loop nest where it is used.
static mlir::LogicalResult VerifyNoWriteBetween(
mlir::StringAttr buffer_name, const Buffer &buffer,
const ProgramPoint &from, const ProgramPoint &to, MappingAttr layout,
const ComputeOpInstance &allowed_write,
const IterationSpaceAnalysis &iteration_spaces,
const StorageAnalysis &storage_analysis,
const SequenceAnalysis &sequence_analysis) {
int num_common_loops = from.NumCommonLoops(to);
for (auto [write_op, write_pos] : buffer.writes()) {
const IterationSpace &iter_space = iteration_spaces.Get(write_op);
if (write_op == allowed_write) continue;
// Check if the write occurs before `from`.
if (sequence_analysis.IsAfter(from, write_op)) {
int write_common_loops = iter_space.NumCommonLoops(from.loop_nest());
if (write_common_loops <= num_common_loops) continue;
const ValueStorage &value_storage =
storage_analysis.GetStorage(write_op.Result(write_pos));
// We consider that there is no overwrite if the write if before `from`
// and layouts are the same.
if (layout == nullptr || value_storage.layout() == nullptr ||
value_storage.layout().ResizeUseDomain(write_common_loops) ==
layout.ResizeUseDomain(write_common_loops)) {
continue;
}
} else if (sequence_analysis.IsBefore(to, write_op)) {
int write_common_loops = iter_space.NumCommonLoops(to.loop_nest());
if (write_common_loops <= num_common_loops) continue;
}
mlir::InFlightDiagnostic diag =
write_op.EmitError() << "operation overwrites a value stored in buffer "
<< buffer_name << " before it is used";
if (from.operation() == nullptr) {
diag.attachNote(write_op.program()->getLoc())
<< "value stored before entering sair program";
} else {
from.operation().AttachNote(diag) << "value stored here";
}
if (to.operation() == nullptr) {
diag.attachNote(write_op.program()->getLoc())
<< "value used after exiting sair program";
} else {
to.operation().AttachNote(diag) << "value used here";
}
return mlir::failure();
}
return mlir::success();
}
// Verifies that `value` storage is not overwritten by an operation between the
// operation that stores the value in `buffer` and `use`.
static mlir::LogicalResult VerifyValueNotOverwritten(
mlir::StringAttr buffer_name, const Buffer &buffer, ResultInstance value,
ProgramPoint use, const LoopFusionAnalysis &fusion_analysis,
const IterationSpaceAnalysis &iteration_spaces,
const StorageAnalysis &storage_analysis,
const SequenceAnalysis &sequence_analysis) {
// Mark visited fby operations to avoid infinite loops.
llvm::DenseSet<OpInstance> visited_fby;
// Allow the use to overwritte the buffer in order to support in-place
// updates.
ComputeOpInstance allowed_write = use.operation();
// Walk producers of `value` to find program points where it is stored in its
// buffer. Maintain a work list of producers to process. For each, {value,
// use} in the work-list, we must verify that there is no write to `buffer`
// between `value` and `use`.
llvm::SmallVector<std::pair<ResultInstance, ProgramPoint>> work_list;
work_list.push_back({value, use});
while (!work_list.empty()) {
auto [value, use_point] = work_list.pop_back_val();
OpInstance defining_op = value.defining_op();
const IterationSpace &iter_space = iteration_spaces.Get(defining_op);
if (auto producer = defining_op.dyn_cast<ComputeOpInstance>()) {
ProgramPoint def_point(producer, Direction::kAfter,
iter_space.loop_names());
const ValueStorage &storage = storage_analysis.GetStorage(value);
if (mlir::failed(VerifyNoWriteBetween(
buffer_name, buffer, def_point, use_point, storage.layout(),
allowed_write, iteration_spaces, storage_analysis,
sequence_analysis))) {
return mlir::failure();
}
continue;
}
mlir::Operation *concrete_op = defining_op.GetDuplicatedOp();
if (auto proj = dyn_cast<SairProjLastOp>(concrete_op)) {
auto value = OperandInstance(proj.Value(), defining_op).GetValue();
if (value.has_value()) {
work_list.emplace_back(*value, use_point);
}
} else if (auto proj = dyn_cast<SairProjAnyOp>(concrete_op)) {
auto value = OperandInstance(proj.Value(), defining_op).GetValue();
if (value.has_value()) {
work_list.emplace_back(*value, use_point);
}
} else if (auto from_memref = dyn_cast<SairFromMemRefOp>(concrete_op)) {
MappingAttr layout = FromToMemRefLayout(from_memref, iter_space);
ProgramPoint before_program(defining_op.program(), Direction::kBefore);
if (mlir::failed(VerifyNoWriteBetween(buffer_name, buffer, before_program,
use_point, layout, allowed_write,
iteration_spaces, storage_analysis,
sequence_analysis))) {
return mlir::failure();
}
} else if (auto fby = dyn_cast<SairFbyOp>(concrete_op)) {
// Find outermost loop that iterate along fby dimensions.
MappingAttr mapping_to_loops = iter_space.MappingToLoops();
auto it = llvm::find_if(mapping_to_loops, [&](MappingExpr expr) {
return expr.MinDomainSize() >= fby.getParallelDomain().size();
});
int first_carry_loop = std::distance(mapping_to_loops.begin(), it);
// Ensure that there is no write between init and the use. We trim
// use_loops to remove dependency-carrying dimensions as we are only going
// to use init at the first iteration.
ProgramPoint init_use_point = use_point;
if (init_use_point.loop_nest().size() > first_carry_loop &&
init_use_point.loop_nest()[first_carry_loop] ==
iter_space.loop_names()[first_carry_loop]) {
init_use_point.TrimLoopNest(first_carry_loop);
}
auto init = OperandInstance(fby.Init(), defining_op).GetValue();
if (init.has_value()) {
work_list.emplace_back(*init, init_use_point);
}
// Ensure that there is no write between the value produced at the last
// iteration of the loop nest and the end of the loop nest.
if (!visited_fby.insert(defining_op).second) continue;
// Case where there are no dependency-carrying dimension.
if (first_carry_loop == iter_space.loop_names().size()) continue;
// Ensure that there is no write between the produce of fby value and the
// end of dependency-carrying dimensions.
mlir::StringAttr carry_loop_name =
iter_space.loop_names()[first_carry_loop];
const LoopFusionClass &carry_loop_class =
fusion_analysis.GetClass(carry_loop_name);
auto value = OperandInstance(fby.Value(), defining_op).GetValue();
if (value.has_value()) {
work_list.emplace_back(*value, carry_loop_class.EndPoint());
}
} else {
llvm_unreachable("unexpected operation");
}
}
return mlir::success();
}
// Verifies that values are not overwritten by another operation before they are
// used.
mlir::LogicalResult VerifyValuesNotOverwritten(
const LoopFusionAnalysis &fusion_analysis,
const IterationSpaceAnalysis &iteration_spaces,
const StorageAnalysis &storage_analysis,
const SequenceAnalysis &sequence_analysis) {
// Ensure that no operation is writting in buffers between the moment
// where a value is written and the moment where a value is read.
for (const auto &[name_attr, buffer] : storage_analysis.buffers()) {
auto buffer_name = name_attr.cast<mlir::StringAttr>();
for (auto [op, operand_pos] : buffer.reads()) {
const IterationSpace &iter_space = iteration_spaces.Get(op);
auto operand = op.Operand(operand_pos).GetValue();
if (!operand.has_value()) continue;
ProgramPoint use_point(op, Direction::kBefore, iter_space.loop_names());
if (mlir::failed(VerifyValueNotOverwritten(
buffer_name, buffer, *operand, use_point, fusion_analysis,
iteration_spaces, storage_analysis, sequence_analysis))) {
return mlir::failure();
}
}
// If the buffer is used in a to_memref operation, ensure that the output is
// not overwritten.
if (!buffer.is_external()) continue;
auto to_memref =
dyn_cast<SairToMemRefOp>(buffer.import_op().getOperation());
if (to_memref == nullptr) continue;
ProgramPoint after_program(cast<SairProgramOp>(to_memref->getParentOp()),
Direction::kAfter);
auto op_instance = OpInstance(cast<SairOp>(to_memref.getOperation()));
auto value = OperandInstance(to_memref.Value(), op_instance).GetValue();
if (!value.has_value()) continue;
if (mlir::failed(VerifyValueNotOverwritten(
buffer_name, buffer, *value, after_program, fusion_analysis,
iteration_spaces, storage_analysis, sequence_analysis))) {
return mlir::failure();
}
}
return mlir::success();
}
// Ensures that communication between producers and users only occurs within the