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+/*
+ * Copyright (C) 2016 The Android Open Source Project
+ *
+ * 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.
+ */
+
+#ifndef ART_COMPILER_OPTIMIZING_SCHEDULER_H_
+#define ART_COMPILER_OPTIMIZING_SCHEDULER_H_
+
+#include <fstream>
+
+#include "base/time_utils.h"
+#include "driver/compiler_driver.h"
+#include "nodes.h"
+#include "optimization.h"
+
+namespace art {
+
+// General description of instruction scheduling.
+//
+// This pass tries to improve the quality of the generated code by reordering
+// instructions in the graph to avoid execution delays caused by execution
+// dependencies.
+// Currently, scheduling is performed at the block level, so no `HInstruction`
+// ever leaves its block in this pass.
+//
+// The scheduling process iterates through blocks in the graph. For blocks that
+// we can and want to schedule:
+// 1) Build a dependency graph for instructions.
+// It includes data dependencies (inputs/uses), but also environment
+// dependencies and side-effect dependencies.
+// 2) Schedule the dependency graph.
+// This is a topological sort of the dependency graph, using heuristics to
+// decide what node to scheduler first when there are multiple candidates.
+//
+// A few factors impacting the quality of the scheduling are:
+// - The heuristics used to decide what node to schedule in the topological sort
+// when there are multiple valid candidates. There is a wide range of
+// complexity possible here, going from a simple model only considering
+// latencies, to a super detailed CPU pipeline model.
+// - Fewer dependencies in the dependency graph give more freedom for the
+// scheduling heuristics. For example de-aliasing can allow possibilities for
+// reordering of memory accesses.
+// - The level of abstraction of the IR. It is easier to evaluate scheduling for
+// IRs that translate to a single assembly instruction than for IRs
+// that generate multiple assembly instructions or generate different code
+// depending on properties of the IR.
+// - Scheduling is performed before register allocation, it is not aware of the
+// impact of moving instructions on register allocation.
+//
+//
+// The scheduling code uses the terms predecessors, successors, and dependencies.
+// This can be confusing at times, so here are clarifications.
+// These terms are used from the point of view of the program dependency graph. So
+// the inputs of an instruction are part of its dependencies, and hence part its
+// predecessors. So the uses of an instruction are (part of) its successors.
+// (Side-effect dependencies can yield predecessors or successors that are not
+// inputs or uses.)
+//
+// Here is a trivial example. For the Java code:
+//
+// int a = 1 + 2;
+//
+// we would have the instructions
+//
+// i1 HIntConstant 1
+// i2 HIntConstant 2
+// i3 HAdd [i1,i2]
+//
+// `i1` and `i2` are predecessors of `i3`.
+// `i3` is a successor of `i1` and a successor of `i2`.
+// In a scheduling graph for this code we would have three nodes `n1`, `n2`,
+// and `n3` (respectively for instructions `i1`, `i1`, and `i3`).
+// Conceptually the program dependency graph for this would contain two edges
+//
+// n1 -> n3
+// n2 -> n3
+//
+// Since we schedule backwards (starting from the last instruction in each basic
+// block), the implementation of nodes keeps a list of pointers their
+// predecessors. So `n3` would keep pointers to its predecessors `n1` and `n2`.
+//
+// Node dependencies are also referred to from the program dependency graph
+// point of view: we say that node `B` immediately depends on `A` if there is an
+// edge from `A` to `B` in the program dependency graph. `A` is a predecessor of
+// `B`, `B` is a successor of `A`. In the example above `n3` depends on `n1` and
+// `n2`.
+// Since nodes in the scheduling graph keep a list of their predecessors, node
+// `B` will have a pointer to its predecessor `A`.
+// As we schedule backwards, `B` will be selected for scheduling before `A` is.
+//
+// So the scheduling for the example above could happen as follow
+//
+// |---------------------------+------------------------|
+// | candidates for scheduling | instructions scheduled |
+// | --------------------------+------------------------|
+//
+// The only node without successors is `n3`, so it is the only initial
+// candidate.
+//
+// | n3 | (none) |
+//
+// We schedule `n3` as the last (and only) instruction. All its predecessors
+// that do not have any unscheduled successors become candidate. That is, `n1`
+// and `n2` become candidates.
+//
+// | n1, n2 | n3 |
+//
+// One of the candidates is selected. In practice this is where scheduling
+// heuristics kick in, to decide which of the candidates should be selected.
+// In this example, let it be `n1`. It is scheduled before previously scheduled
+// nodes (in program order). There are no other nodes to add to the list of
+// candidates.
+//
+// | n2 | n1 |
+// | | n3 |
+//
+// The only candidate available for scheduling is `n2`. Schedule it before
+// (in program order) the previously scheduled nodes.
+//
+// | (none) | n2 |
+// | | n1 |
+// | | n3 |
+// |---------------------------+------------------------|
+//
+// So finally the instructions will be executed in the order `i2`, `i1`, and `i3`.
+// In this trivial example, it does not matter which of `i1` and `i2` is
+// scheduled first since they are constants. However the same process would
+// apply if `i1` and `i2` were actual operations (for example `HMul` and `HDiv`).
+
+// Set to true to have instruction scheduling dump scheduling graphs to the file
+// `scheduling_graphs.dot`. See `SchedulingGraph::DumpAsDotGraph()`.
+static constexpr bool kDumpDotSchedulingGraphs = false;
+
+// Typically used as a default instruction latency.
+static constexpr uint32_t kGenericInstructionLatency = 1;
+
+class HScheduler;
+
+/**
+ * A node representing an `HInstruction` in the `SchedulingGraph`.
+ */
+class SchedulingNode : public ArenaObject<kArenaAllocScheduler> {
+ public:
+ SchedulingNode(HInstruction* instr, ArenaAllocator* arena, bool is_scheduling_barrier)
+ : latency_(0),
+ internal_latency_(0),
+ critical_path_(0),
+ instruction_(instr),
+ is_scheduling_barrier_(is_scheduling_barrier),
+ data_predecessors_(arena->Adapter(kArenaAllocScheduler)),
+ other_predecessors_(arena->Adapter(kArenaAllocScheduler)),
+ num_unscheduled_successors_(0) {
+ data_predecessors_.reserve(kPreallocatedPredecessors);
+ }
+
+ void AddDataPredecessor(SchedulingNode* predecessor) {
+ data_predecessors_.push_back(predecessor);
+ predecessor->num_unscheduled_successors_++;
+ }
+
+ void AddOtherPredecessor(SchedulingNode* predecessor) {
+ other_predecessors_.push_back(predecessor);
+ predecessor->num_unscheduled_successors_++;
+ }
+
+ void DecrementNumberOfUnscheduledSuccessors() {
+ num_unscheduled_successors_--;
+ }
+
+ void MaybeUpdateCriticalPath(uint32_t other_critical_path) {
+ critical_path_ = std::max(critical_path_, other_critical_path);
+ }
+
+ bool HasUnscheduledSuccessors() const {
+ return num_unscheduled_successors_ != 0;
+ }
+
+ HInstruction* GetInstruction() const { return instruction_; }
+ uint32_t GetLatency() const { return latency_; }
+ void SetLatency(uint32_t latency) { latency_ = latency; }
+ uint32_t GetInternalLatency() const { return internal_latency_; }
+ void SetInternalLatency(uint32_t internal_latency) { internal_latency_ = internal_latency; }
+ uint32_t GetCriticalPath() const { return critical_path_; }
+ bool IsSchedulingBarrier() const { return is_scheduling_barrier_; }
+ const ArenaVector<SchedulingNode*>& GetDataPredecessors() const { return data_predecessors_; }
+ const ArenaVector<SchedulingNode*>& GetOtherPredecessors() const { return other_predecessors_; }
+
+ private:
+ // The latency of this node. It represents the latency between the moment the
+ // last instruction for this node has executed to the moment the result
+ // produced by this node is available to users.
+ uint32_t latency_;
+ // This represents the time spent *within* the generated code for this node.
+ // It should be zero for nodes that only generate a single instruction.
+ uint32_t internal_latency_;
+
+ // The critical path from this instruction to the end of scheduling. It is
+ // used by the scheduling heuristics to measure the priority of this instruction.
+ // It is defined as
+ // critical_path_ = latency_ + max((use.internal_latency_ + use.critical_path_) for all uses)
+ // (Note that here 'uses' is equivalent to 'data successors'. Also see comments in
+ // `HScheduler::Schedule(SchedulingNode* scheduling_node)`).
+ uint32_t critical_path_;
+
+ // The instruction that this node represents.
+ HInstruction* const instruction_;
+
+ // If a node is scheduling barrier, other nodes cannot be scheduled before it.
+ const bool is_scheduling_barrier_;
+
+ // The lists of predecessors. They cannot be scheduled before this node. Once
+ // this node is scheduled, we check whether any of its predecessors has become a
+ // valid candidate for scheduling.
+ // Predecessors in `data_predecessors_` are data dependencies. Those in
+ // `other_predecessors_` contain side-effect dependencies, environment
+ // dependencies, and scheduling barrier dependencies.
+ ArenaVector<SchedulingNode*> data_predecessors_;
+ ArenaVector<SchedulingNode*> other_predecessors_;
+
+ // The number of unscheduled successors for this node. This number is
+ // decremented as successors are scheduled. When it reaches zero this node
+ // becomes a valid candidate to schedule.
+ uint32_t num_unscheduled_successors_;
+
+ static constexpr size_t kPreallocatedPredecessors = 4;
+};
+
+/*
+ * Directed acyclic graph for scheduling.
+ */
+class SchedulingGraph : public ValueObject {
+ public:
+ SchedulingGraph(const HScheduler* scheduler, ArenaAllocator* arena)
+ : scheduler_(scheduler),
+ arena_(arena),
+ contains_scheduling_barrier_(false),
+ nodes_map_(arena_->Adapter(kArenaAllocScheduler)) {}
+
+ SchedulingNode* AddNode(HInstruction* instr, bool is_scheduling_barrier = false) {
+ SchedulingNode* node = new (arena_) SchedulingNode(instr, arena_, is_scheduling_barrier);
+ nodes_map_.Insert(std::make_pair(instr, node));
+ contains_scheduling_barrier_ |= is_scheduling_barrier;
+ AddDependencies(instr, is_scheduling_barrier);
+ return node;
+ }
+
+ void Clear() {
+ nodes_map_.Clear();
+ contains_scheduling_barrier_ = false;
+ }
+
+ SchedulingNode* GetNode(const HInstruction* instr) const {
+ auto it = nodes_map_.Find(instr);
+ if (it == nodes_map_.end()) {
+ return nullptr;
+ } else {
+ return it->second;
+ }
+ }
+
+ bool IsSchedulingBarrier(const HInstruction* instruction) const;
+
+ bool HasImmediateDataDependency(const SchedulingNode* node, const SchedulingNode* other) const;
+ bool HasImmediateDataDependency(const HInstruction* node, const HInstruction* other) const;
+ bool HasImmediateOtherDependency(const SchedulingNode* node, const SchedulingNode* other) const;
+ bool HasImmediateOtherDependency(const HInstruction* node, const HInstruction* other) const;
+
+ size_t Size() const {
+ return nodes_map_.Size();
+ }
+
+ // Dump the scheduling graph, in dot file format, appending it to the file
+ // `scheduling_graphs.dot`.
+ void DumpAsDotGraph(const std::string& description,
+ const ArenaVector<SchedulingNode*>& initial_candidates);
+
+ protected:
+ void AddDependency(SchedulingNode* node, SchedulingNode* dependency, bool is_data_dependency);
+ void AddDataDependency(SchedulingNode* node, SchedulingNode* dependency) {
+ AddDependency(node, dependency, /*is_data_dependency*/true);
+ }
+ void AddOtherDependency(SchedulingNode* node, SchedulingNode* dependency) {
+ AddDependency(node, dependency, /*is_data_dependency*/false);
+ }
+
+ // Add dependencies nodes for the given `HInstruction`: inputs, environments, and side-effects.
+ void AddDependencies(HInstruction* instruction, bool is_scheduling_barrier = false);
+
+ const HScheduler* const scheduler_;
+
+ ArenaAllocator* const arena_;
+
+ bool contains_scheduling_barrier_;
+
+ ArenaHashMap<const HInstruction*, SchedulingNode*> nodes_map_;
+};
+
+/*
+ * The visitors derived from this base class are used by schedulers to evaluate
+ * the latencies of `HInstruction`s.
+ */
+class SchedulingLatencyVisitor : public HGraphDelegateVisitor {
+ public:
+ // This class and its sub-classes will never be used to drive a visit of an
+ // `HGraph` but only to visit `HInstructions` one at a time, so we do not need
+ // to pass a valid graph to `HGraphDelegateVisitor()`.
+ SchedulingLatencyVisitor() : HGraphDelegateVisitor(nullptr) {}
+
+ void VisitInstruction(HInstruction* instruction) OVERRIDE {
+ LOG(FATAL) << "Error visiting " << instruction->DebugName() << ". "
+ "Architecture-specific scheduling latency visitors must handle all instructions"
+ " (potentially by overriding the generic `VisitInstruction()`.";
+ UNREACHABLE();
+ }
+
+ void Visit(HInstruction* instruction) {
+ instruction->Accept(this);
+ }
+
+ void CalculateLatency(SchedulingNode* node) {
+ // By default nodes have no internal latency.
+ last_visited_internal_latency_ = 0;
+ Visit(node->GetInstruction());
+ }
+
+ uint32_t GetLastVisitedLatency() const { return last_visited_latency_; }
+ uint32_t GetLastVisitedInternalLatency() const { return last_visited_internal_latency_; }
+
+ protected:
+ // The latency of the most recent visited SchedulingNode.
+ // This is for reporting the latency value to the user of this visitor.
+ uint32_t last_visited_latency_;
+ // This represents the time spent *within* the generated code for the most recent visited
+ // SchedulingNode. This is for reporting the internal latency value to the user of this visitor.
+ uint32_t last_visited_internal_latency_;
+};
+
+class SchedulingNodeSelector : public ArenaObject<kArenaAllocScheduler> {
+ public:
+ virtual SchedulingNode* PopHighestPriorityNode(ArenaVector<SchedulingNode*>* nodes,
+ const SchedulingGraph& graph) = 0;
+ virtual ~SchedulingNodeSelector() {}
+ protected:
+ static void DeleteNodeAtIndex(ArenaVector<SchedulingNode*>* nodes, size_t index) {
+ (*nodes)[index] = nodes->back();
+ nodes->pop_back();
+ }
+};
+
+/*
+ * Select a `SchedulingNode` at random within the candidates.
+ */
+class RandomSchedulingNodeSelector : public SchedulingNodeSelector {
+ public:
+ explicit RandomSchedulingNodeSelector() : seed_(0) {
+ seed_ = static_cast<uint32_t>(NanoTime());
+ srand(seed_);
+ }
+
+ SchedulingNode* PopHighestPriorityNode(ArenaVector<SchedulingNode*>* nodes,
+ const SchedulingGraph& graph) OVERRIDE {
+ UNUSED(graph);
+ DCHECK(!nodes->empty());
+ size_t select = rand_r(&seed_) % nodes->size();
+ SchedulingNode* select_node = (*nodes)[select];
+ DeleteNodeAtIndex(nodes, select);
+ return select_node;
+ }
+
+ uint32_t seed_;
+};
+
+/*
+ * Select a `SchedulingNode` according to critical path information,
+ * with heuristics to favor certain instruction patterns like materialized condition.
+ */
+class CriticalPathSchedulingNodeSelector : public SchedulingNodeSelector {
+ public:
+ CriticalPathSchedulingNodeSelector() : prev_select_(nullptr) {}
+
+ SchedulingNode* PopHighestPriorityNode(ArenaVector<SchedulingNode*>* nodes,
+ const SchedulingGraph& graph) OVERRIDE;
+
+ protected:
+ SchedulingNode* GetHigherPrioritySchedulingNode(SchedulingNode* candidate,
+ SchedulingNode* check) const;
+
+ SchedulingNode* SelectMaterializedCondition(ArenaVector<SchedulingNode*>* nodes,
+ const SchedulingGraph& graph) const;
+
+ private:
+ const SchedulingNode* prev_select_;
+};
+
+class HScheduler {
+ public:
+ HScheduler(ArenaAllocator* arena,
+ SchedulingLatencyVisitor* latency_visitor,
+ SchedulingNodeSelector* selector)
+ : arena_(arena),
+ latency_visitor_(latency_visitor),
+ selector_(selector),
+ only_optimize_loop_blocks_(true),
+ scheduling_graph_(this, arena),
+ candidates_(arena_->Adapter(kArenaAllocScheduler)) {}
+ virtual ~HScheduler() {}
+
+ void Schedule(HGraph* graph);
+
+ void SetOnlyOptimizeLoopBlocks(bool loop_only) { only_optimize_loop_blocks_ = loop_only; }
+
+ // Instructions can not be rescheduled across a scheduling barrier.
+ virtual bool IsSchedulingBarrier(const HInstruction* instruction) const;
+
+ protected:
+ void Schedule(HBasicBlock* block);
+ void Schedule(SchedulingNode* scheduling_node);
+ void Schedule(HInstruction* instruction);
+
+ // Any instruction returning `false` via this method will prevent its
+ // containing basic block from being scheduled.
+ // This method is used to restrict scheduling to instructions that we know are
+ // safe to handle.
+ virtual bool IsSchedulable(const HInstruction* instruction) const;
+ bool IsSchedulable(const HBasicBlock* block) const;
+
+ void CalculateLatency(SchedulingNode* node) {
+ latency_visitor_->CalculateLatency(node);
+ node->SetLatency(latency_visitor_->GetLastVisitedLatency());
+ node->SetInternalLatency(latency_visitor_->GetLastVisitedInternalLatency());
+ }
+
+ ArenaAllocator* const arena_;
+ SchedulingLatencyVisitor* const latency_visitor_;
+ SchedulingNodeSelector* const selector_;
+ bool only_optimize_loop_blocks_;
+
+ // We instantiate the members below as part of this class to avoid
+ // instantiating them locally for every chunk scheduled.
+ SchedulingGraph scheduling_graph_;
+ // A pointer indicating where the next instruction to be scheduled will be inserted.
+ HInstruction* cursor_;
+ // The list of candidates for scheduling. A node becomes a candidate when all
+ // its predecessors have been scheduled.
+ ArenaVector<SchedulingNode*> candidates_;
+
+ private:
+ DISALLOW_COPY_AND_ASSIGN(HScheduler);
+};
+
+inline bool SchedulingGraph::IsSchedulingBarrier(const HInstruction* instruction) const {
+ return scheduler_->IsSchedulingBarrier(instruction);
+}
+
+class HInstructionScheduling : public HOptimization {
+ public:
+ HInstructionScheduling(HGraph* graph, InstructionSet instruction_set)
+ : HOptimization(graph, kInstructionScheduling),
+ instruction_set_(instruction_set) {}
+
+ void Run() {
+ Run(/*only_optimize_loop_blocks*/ true, /*schedule_randomly*/ false);
+ }
+ void Run(bool only_optimize_loop_blocks, bool schedule_randomly);
+
+ static constexpr const char* kInstructionScheduling = "scheduler";
+
+ const InstructionSet instruction_set_;
+
+ private:
+ DISALLOW_COPY_AND_ASSIGN(HInstructionScheduling);
+};
+
+} // namespace art
+
+#endif // ART_COMPILER_OPTIMIZING_SCHEDULER_H_