namespace {
-static cl::opt<bool> SampleProfileEvenCountDistribution(
- "sample-profile-even-count-distribution", cl::init(true), cl::Hidden,
- cl::desc("Try to evenly distribute counts when there are multiple equally "
+static cl::opt<bool> SampleProfileEvenFlowDistribution(
+ "sample-profile-even-flow-distribution", cl::init(true), cl::Hidden,
+ cl::desc("Try to evenly distribute flow when there are multiple equally "
"likely options."));
-static cl::opt<unsigned> SampleProfileMaxDfsCalls(
- "sample-profile-max-dfs-calls", cl::init(10), cl::Hidden,
- cl::desc("Maximum number of dfs iterations for even count distribution."));
+static cl::opt<bool> SampleProfileRebalanceUnknown(
+ "sample-profile-rebalance-unknown", cl::init(true), cl::Hidden,
+ cl::desc("Evenly re-distribute flow among unknown subgraphs."));
-static cl::opt<unsigned> SampleProfileProfiCostInc(
- "sample-profile-profi-cost-inc", cl::init(10), cl::Hidden,
- cl::desc("A cost of increasing a block's count by one."));
+static cl::opt<bool> SampleProfileJoinIslands(
+ "sample-profile-join-islands", cl::init(true), cl::Hidden,
+ cl::desc("Join isolated components having positive flow."));
-static cl::opt<unsigned> SampleProfileProfiCostDec(
- "sample-profile-profi-cost-dec", cl::init(20), cl::Hidden,
- cl::desc("A cost of decreasing a block's count by one."));
+static cl::opt<unsigned> SampleProfileProfiCostBlockInc(
+ "sample-profile-profi-cost-block-inc", cl::init(10), cl::Hidden,
+ cl::desc("The cost of increasing a block's count by one."));
-static cl::opt<unsigned> SampleProfileProfiCostIncZero(
- "sample-profile-profi-cost-inc-zero", cl::init(11), cl::Hidden,
- cl::desc("A cost of increasing a count of zero-weight block by one."));
+static cl::opt<unsigned> SampleProfileProfiCostBlockDec(
+ "sample-profile-profi-cost-block-dec", cl::init(20), cl::Hidden,
+ cl::desc("The cost of decreasing a block's count by one."));
-static cl::opt<unsigned> SampleProfileProfiCostIncEntry(
- "sample-profile-profi-cost-inc-entry", cl::init(40), cl::Hidden,
- cl::desc("A cost of increasing the entry block's count by one."));
+static cl::opt<unsigned> SampleProfileProfiCostBlockEntryInc(
+ "sample-profile-profi-cost-block-entry-inc", cl::init(40), cl::Hidden,
+ cl::desc("The cost of increasing the entry block's count by one."));
-static cl::opt<unsigned> SampleProfileProfiCostDecEntry(
- "sample-profile-profi-cost-dec-entry", cl::init(10), cl::Hidden,
- cl::desc("A cost of decreasing the entry block's count by one."));
+static cl::opt<unsigned> SampleProfileProfiCostBlockEntryDec(
+ "sample-profile-profi-cost-block-entry-dec", cl::init(10), cl::Hidden,
+ cl::desc("The cost of decreasing the entry block's count by one."));
+
+static cl::opt<unsigned> SampleProfileProfiCostBlockZeroInc(
+ "sample-profile-profi-cost-block-zero-inc", cl::init(11), cl::Hidden,
+ cl::desc("The cost of increasing a count of zero-weight block by one."));
+
+static cl::opt<unsigned> SampleProfileProfiCostBlockUnknownInc(
+ "sample-profile-profi-cost-block-unknown-inc", cl::init(0), cl::Hidden,
+ cl::desc("The cost of increasing an unknown block's count by one."));
/// A value indicating an infinite flow/capacity/weight of a block/edge.
/// Not using numeric_limits<int64_t>::max(), as the values can be summed up
/// minimum total cost respecting the given edge capacities.
class MinCostMaxFlow {
public:
+ MinCostMaxFlow(const ProfiParams &Params) : Params(Params) {}
+
// Initialize algorithm's data structures for a network of a given size.
void initialize(uint64_t NodeCount, uint64_t SourceNode, uint64_t SinkNode) {
Source = SourceNode;
Nodes = std::vector<Node>(NodeCount);
Edges = std::vector<std::vector<Edge>>(NodeCount, std::vector<Edge>());
- if (SampleProfileEvenCountDistribution)
+ if (Params.EvenFlowDistribution)
AugmentingEdges =
std::vector<std::vector<Edge *>>(NodeCount, std::vector<Edge *>());
}
return Flow;
}
- /// A cost of taking an unlikely jump.
- static constexpr int64_t AuxCostUnlikely = ((int64_t)1) << 30;
- /// Minimum BaseDistance for the jump distance values in island joining.
- static constexpr uint64_t MinBaseDistance = 10000;
-
private:
/// Iteratively find an augmentation path/dag in the network and send the
/// flow along its edges. The method returns the number of applied iterations.
uint64_t PathCapacity = computeAugmentingPathCapacity();
while (PathCapacity > 0) {
bool Progress = false;
- if (SampleProfileEvenCountDistribution) {
+ if (Params.EvenFlowDistribution) {
// Identify node/edge candidates for augmentation
identifyShortestEdges(PathCapacity);
// from Source to Target; it follows from inequalities
// Dist[Source, Target] >= Dist[Source, V] + Dist[V, Target]
// >= Dist[Source, V]
- if (!SampleProfileEvenCountDistribution && Nodes[Target].Distance == 0)
+ if (!Params.EvenFlowDistribution && Nodes[Target].Distance == 0)
break;
if (Nodes[Src].Distance > Nodes[Target].Distance)
continue;
if (Edge.OnShortestPath) {
// If we haven't seen Edge.Dst so far, continue DFS search there
- if (Dst.Discovery == 0 && Dst.NumCalls < SampleProfileMaxDfsCalls) {
+ if (Dst.Discovery == 0 && Dst.NumCalls < MaxDfsCalls) {
Dst.Discovery = ++Time;
Stack.emplace(Edge.Dst, 0);
Dst.NumCalls++;
}
}
+ /// Maximum number of DFS iterations for DAG finding.
+ static constexpr uint64_t MaxDfsCalls = 10;
+
/// A node in a flow network.
struct Node {
/// The cost of the cheapest path from the source to the current node.
uint64_t Target;
/// Augmenting edges.
std::vector<std::vector<Edge *>> AugmentingEdges;
+ /// Params for flow computation.
+ const ProfiParams &Params;
};
/// A post-processing adjustment of control flow. It applies two steps by
///
class FlowAdjuster {
public:
- FlowAdjuster(FlowFunction &Func) : Func(Func) {
+ FlowAdjuster(const ProfiParams &Params, FlowFunction &Func)
+ : Params(Params), Func(Func) {
assert(Func.Blocks[Func.Entry].isEntry() &&
"incorrect index of the entry block");
}
// Run the post-processing
void run() {
- /// Adjust the flow to get rid of isolated components.
- joinIsolatedComponents();
+ if (Params.JoinIslands) {
+ /// Adjust the flow to get rid of isolated components.
+ joinIsolatedComponents();
+ }
- /// Rebalance the flow inside unknown subgraphs.
- rebalanceUnknownSubgraphs();
+ if (Params.RebalanceUnknown) {
+ /// Rebalance the flow inside unknown subgraphs.
+ rebalanceUnknownSubgraphs();
+ }
}
private:
/// To capture this objective with integer distances, we round off fractional
/// parts to a multiple of 1 / BaseDistance.
int64_t jumpDistance(FlowJump *Jump) const {
+ if (Jump->IsUnlikely)
+ return Params.CostUnlikely;
+
uint64_t BaseDistance =
- std::max(MinCostMaxFlow::MinBaseDistance,
+ std::max(FlowAdjuster::MinBaseDistance,
std::min(Func.Blocks[Func.Entry].Flow,
- MinCostMaxFlow::AuxCostUnlikely / NumBlocks()));
- if (Jump->IsUnlikely)
- return MinCostMaxFlow::AuxCostUnlikely;
+ Params.CostUnlikely / NumBlocks()));
if (Jump->Flow > 0)
return BaseDistance + BaseDistance / Jump->Flow;
return BaseDistance * NumBlocks();
bool canRebalanceAtRoot(const FlowBlock *SrcBlock) {
// Do not attempt to find unknown subgraphs from an unknown or a
// zero-flow block
- if (SrcBlock->UnknownWeight || SrcBlock->Flow == 0)
+ if (SrcBlock->HasUnknownWeight || SrcBlock->Flow == 0)
return false;
// Do not attempt to process subgraphs from a block w/o unknown sucessors
bool HasUnknownSuccs = false;
for (auto *Jump : SrcBlock->SuccJumps) {
- if (Func.Blocks[Jump->Target].UnknownWeight) {
+ if (Func.Blocks[Jump->Target].HasUnknownWeight) {
HasUnknownSuccs = true;
break;
}
continue;
// Process block Dst
Visited[Dst] = true;
- if (!Func.Blocks[Dst].UnknownWeight) {
+ if (!Func.Blocks[Dst].HasUnknownWeight) {
KnownDstBlocks.push_back(&Func.Blocks[Dst]);
} else {
Queue.push(Dst);
return false;
// Ignore jumps out of SrcBlock to known blocks
- if (!JumpTarget->UnknownWeight && JumpSource == SrcBlock)
+ if (!JumpTarget->HasUnknownWeight && JumpSource == SrcBlock)
return true;
// Ignore jumps to known blocks with zero flow
- if (!JumpTarget->UnknownWeight && JumpTarget->Flow == 0)
+ if (!JumpTarget->HasUnknownWeight && JumpTarget->Flow == 0)
return true;
return false;
break;
// Keep an acyclic order of unknown blocks
- if (Block->UnknownWeight && Block != SrcBlock)
+ if (Block->HasUnknownWeight && Block != SrcBlock)
AcyclicOrder.push_back(Block);
// Add to the queue all successors with zero local in-degree
// Ditribute flow from the remaining blocks
for (auto *Block : UnknownBlocks) {
- assert(Block->UnknownWeight && "incorrect unknown subgraph");
+ assert(Block->HasUnknownWeight && "incorrect unknown subgraph");
uint64_t BlockFlow = 0;
// Block's flow is the sum of incoming flows
for (auto *Jump : Block->PredJumps) {
/// A constant indicating an arbitrary exit block of a function.
static constexpr uint64_t AnyExitBlock = uint64_t(-1);
+ /// Minimum BaseDistance for the jump distance values in island joining.
+ static constexpr uint64_t MinBaseDistance = 10000;
+ /// Params for flow computation.
+ const ProfiParams &Params;
/// The function.
FlowFunction &Func;
};
/// Every block is split into three nodes that are responsible for (i) an
/// incoming flow, (ii) an outgoing flow, and (iii) penalizing an increase or
/// reduction of the block weight.
-void initializeNetwork(MinCostMaxFlow &Network, FlowFunction &Func) {
+void initializeNetwork(const ProfiParams &Params, MinCostMaxFlow &Network,
+ FlowFunction &Func) {
uint64_t NumBlocks = Func.Blocks.size();
assert(NumBlocks > 1 && "Too few blocks in a function");
LLVM_DEBUG(dbgs() << "Initializing profi for " << NumBlocks << " blocks\n");
// Create three nodes for every block of the function
for (uint64_t B = 0; B < NumBlocks; B++) {
auto &Block = Func.Blocks[B];
- assert((!Block.UnknownWeight || Block.Weight == 0 || Block.isEntry()) &&
+ assert((!Block.HasUnknownWeight || Block.Weight == 0 || Block.isEntry()) &&
"non-zero weight of a block w/o weight except for an entry");
// Split every block into two nodes
// We assume that decreasing block counts is more expensive than increasing,
// and thus, setting separate costs here. In the future we may want to tune
// the relative costs so as to maximize the quality of generated profiles.
- int64_t AuxCostInc = SampleProfileProfiCostInc;
- int64_t AuxCostDec = SampleProfileProfiCostDec;
- if (Block.UnknownWeight) {
+ int64_t AuxCostInc = Params.CostBlockInc;
+ int64_t AuxCostDec = Params.CostBlockDec;
+ if (Block.HasUnknownWeight) {
// Do not penalize changing weights of blocks w/o known profile count
- AuxCostInc = 0;
+ AuxCostInc = Params.CostBlockUnknownInc;
AuxCostDec = 0;
} else {
// Increasing the count for "cold" blocks with zero initial count is more
// expensive than for "hot" ones
if (Block.Weight == 0) {
- AuxCostInc = SampleProfileProfiCostIncZero;
+ AuxCostInc = Params.CostBlockZeroInc;
}
// Modifying the count of the entry block is expensive
if (Block.isEntry()) {
- AuxCostInc = SampleProfileProfiCostIncEntry;
- AuxCostDec = SampleProfileProfiCostDecEntry;
+ AuxCostInc = Params.CostBlockEntryInc;
+ AuxCostDec = Params.CostBlockEntryDec;
}
}
// For blocks with self-edges, do not penalize a reduction of the count,
if (Src != Dst) {
uint64_t SrcOut = 3 * Src + 1;
uint64_t DstIn = 3 * Dst;
- uint64_t Cost = Jump.IsUnlikely ? MinCostMaxFlow::AuxCostUnlikely : 0;
+ uint64_t Cost = Jump.IsUnlikely ? Params.CostUnlikely : 0;
Network.addEdge(SrcOut, DstIn, Cost);
}
}
} // end of anonymous namespace
/// Apply the profile inference algorithm for a given flow function
-void llvm::applyFlowInference(FlowFunction &Func) {
+void llvm::applyFlowInference(const ProfiParams &Params, FlowFunction &Func) {
// Create and apply an inference network model
- auto InferenceNetwork = MinCostMaxFlow();
- initializeNetwork(InferenceNetwork, Func);
+ auto InferenceNetwork = MinCostMaxFlow(Params);
+ initializeNetwork(Params, InferenceNetwork, Func);
InferenceNetwork.run();
// Extract flow values for every block and every edge
extractWeights(InferenceNetwork, Func);
// Post-processing adjustments to the flow
- auto Adjuster = FlowAdjuster(Func);
+ auto Adjuster = FlowAdjuster(Params, Func);
Adjuster.run();
#ifndef NDEBUG
verifyWeights(Func);
#endif
}
+
+/// Apply the profile inference algorithm for a given flow function
+void llvm::applyFlowInference(FlowFunction &Func) {
+ ProfiParams Params;
+ // Set the params from the command-line flags.
+ Params.EvenFlowDistribution = SampleProfileEvenFlowDistribution;
+ Params.RebalanceUnknown = SampleProfileRebalanceUnknown;
+ Params.JoinIslands = SampleProfileJoinIslands;
+ Params.CostBlockInc = SampleProfileProfiCostBlockInc;
+ Params.CostBlockDec = SampleProfileProfiCostBlockDec;
+ Params.CostBlockEntryInc = SampleProfileProfiCostBlockEntryInc;
+ Params.CostBlockEntryDec = SampleProfileProfiCostBlockEntryDec;
+ Params.CostBlockZeroInc = SampleProfileProfiCostBlockZeroInc;
+ Params.CostBlockUnknownInc = SampleProfileProfiCostBlockUnknownInc;
+
+ applyFlowInference(Params, Func);
+}
projects / platform / upstream / llvm.git / commitdiff