//===-- LatencyBenchmarkRunner.cpp ------------------------------*- C++ -*-===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
//===----------------------------------------------------------------------===//

#include "LatencyBenchmarkRunner.h"

#include "BenchmarkRunner.h"
#include "Target.h"
#include "llvm/ADT/Twine.h"
#include "llvm/Support/Error.h"
#include <algorithm>
#include <cmath>

namespace llvm {
namespace exegesis {

LatencyBenchmarkRunner::LatencyBenchmarkRunner(
    const LLVMState &State, InstructionBenchmark::ModeE Mode,
    InstructionBenchmark::ResultAggregationModeE ResultAgg)
    : BenchmarkRunner(State, Mode) {
  assert((Mode == InstructionBenchmark::Latency ||
          Mode == InstructionBenchmark::InverseThroughput) &&
         "invalid mode");
  ResultAggMode = ResultAgg;
}

LatencyBenchmarkRunner::~LatencyBenchmarkRunner() = default;

static double computeVariance(const llvm::SmallVector<int64_t, 4> &Values) {
  if (Values.empty())
    return 0.0;
  double Sum = std::accumulate(Values.begin(), Values.end(), 0.0);

  const double Mean = Sum / Values.size();
  double Ret = 0;
  for (const auto &V : Values) {
    double Delta = V - Mean;
    Ret += Delta * Delta;
  }
  return Ret / Values.size();
}

static int64_t findMin(const llvm::SmallVector<int64_t, 4> &Values) {
  if (Values.empty())
    return 0;
  return *std::min_element(Values.begin(), Values.end());
}

static int64_t findMax(const llvm::SmallVector<int64_t, 4> &Values) {
  if (Values.empty())
    return 0;
  return *std::max_element(Values.begin(), Values.end());
}

static int64_t findMean(const llvm::SmallVector<int64_t, 4> &Values) {
  if (Values.empty())
    return 0;
  return std::accumulate(Values.begin(), Values.end(), 0.0) /
         static_cast<double>(Values.size());
}

Expected<std::vector<BenchmarkMeasure>> LatencyBenchmarkRunner::runMeasurements(
    const FunctionExecutor &Executor) const {
  // Cycle measurements include some overhead from the kernel. Repeat the
  // measure several times and return the aggregated value, as specified by
  // ResultAggMode.
  constexpr const int NumMeasurements = 30;
  llvm::SmallVector<int64_t, 4> AccumulatedValues;
  double MinVariance = std::numeric_limits<double>::infinity();
  const char *CounterName = State.getPfmCounters().CycleCounter;
  // Values count for each run.
  int ValuesCount = 0;
  for (size_t I = 0; I < NumMeasurements; ++I) {
    auto ExpectedCounterValues = Executor.runAndSample(CounterName);
    if (!ExpectedCounterValues)
      return ExpectedCounterValues.takeError();
    ValuesCount = ExpectedCounterValues.get().size();
    if (ValuesCount == 1)
      AccumulatedValues.push_back(ExpectedCounterValues.get()[0]);
    else {
      // We'll keep the reading with lowest variance (ie., most stable)
      double Variance = computeVariance(*ExpectedCounterValues);
      if (MinVariance > Variance) {
        AccumulatedValues = std::move(ExpectedCounterValues.get());
        MinVariance = Variance;
      }
    }
  }

  std::string ModeName;
  switch (Mode) {
  case InstructionBenchmark::Latency:
    ModeName = "latency";
    break;
  case InstructionBenchmark::InverseThroughput:
    ModeName = "inverse_throughput";
    break;
  default:
    break;
  }

  switch (ResultAggMode) {
  case InstructionBenchmark::MinVariance: {
    if (ValuesCount == 1)
      llvm::errs() << "Each sample only has one value. result-aggregation-mode "
                      "of min-variance is probably non-sensical\n";
    std::vector<BenchmarkMeasure> Result;
    Result.reserve(AccumulatedValues.size());
    for (const int64_t Value : AccumulatedValues)
      Result.push_back(BenchmarkMeasure::Create(ModeName, Value));
    return std::move(Result);
  }
  case InstructionBenchmark::Min: {
    std::vector<BenchmarkMeasure> Result;
    Result.push_back(
        BenchmarkMeasure::Create(ModeName, findMin(AccumulatedValues)));
    return std::move(Result);
  }
  case InstructionBenchmark::Max: {
    std::vector<BenchmarkMeasure> Result;
    Result.push_back(
        BenchmarkMeasure::Create(ModeName, findMax(AccumulatedValues)));
    return std::move(Result);
  }
  case InstructionBenchmark::Mean: {
    std::vector<BenchmarkMeasure> Result;
    Result.push_back(
        BenchmarkMeasure::Create(ModeName, findMean(AccumulatedValues)));
    return std::move(Result);
  }
  }
  return llvm::make_error<Failure>(llvm::Twine("Unexpected benchmark mode(")
                                       .concat(std::to_string(Mode))
                                       .concat(" and unexpected ResultAggMode ")
                                       .concat(std::to_string(ResultAggMode)));
}

} // namespace exegesis
} // namespace llvm