main.cpp

#include <pls/pls.h>
#include <pls/internal/helpers/profiler.h>
#include <pls/internal/helpers/mini_benchmark.h>

#include <iostream>
#include <complex>
#include <vector>

static constexpr int CUTOFF = 16;
static constexpr int NUM_ITERATIONS = 1000;
static constexpr int INPUT_SIZE = 8192;
typedef std::vector<std::complex<double>> complex_vector;

void divide(complex_vector::iterator data, int n) {
  complex_vector tmp_odd_elements(n / 2);
  for (int i = 0; i < n / 2; i++) {
    tmp_odd_elements[i] = data[i * 2 + 1];
  }
  for (int i = 0; i < n / 2; i++) {
    data[i] = data[i * 2];
  }
  for (int i = 0; i < n / 2; i++) {
    data[i + n / 2] = tmp_odd_elements[i];
  }
}

void combine(complex_vector::iterator data, int n) {
  for (int i = 0; i < n / 2; i++) {
    std::complex<double> even = data[i];
    std::complex<double> odd = data[i + n / 2];

    // w is the "twiddle-factor".
    // this could be cached, but we run the same 'data_structures' algorithm parallel/serial,
    // so it won't impact the performance comparison.
    std::complex<double> w = exp(std::complex<double>(0, -2. * M_PI * i / n));

    data[i] = even + w * odd;
    data[i + n / 2] = even - w * odd;
  }
}

void fft(complex_vector::iterator data, int n) {
  if (n < 2) {
    return;
  }

  divide(data, n);
  if (n <= CUTOFF) {
    fft(data, n / 2);
    fft(data + n / 2, n / 2);
  } else {
    pls::invoke(
        [&] { fft(data, n / 2); },
        [&] { fft(data + n / 2, n / 2); }
    );
  }
  combine(data, n);
}

complex_vector prepare_input(int input_size) {
  std::vector<double> known_frequencies{2, 11, 52, 88, 256};
  complex_vector data(input_size);

  // Set our input data to match a time series of the known_frequencies.
  // When applying fft to this time-series we should find these frequencies.
  for (int i = 0; i < input_size; i++) {
    data[i] = std::complex<double>(0.0, 0.0);
    for (auto frequencie : known_frequencies) {
      data[i] += sin(2 * M_PI * frequencie * i / input_size);
    }
  }

  return data;
}

int main() {
  PROFILE_ENABLE
  complex_vector initial_input = prepare_input(INPUT_SIZE);

  pls::internal::helpers::run_mini_benchmark([&] {
    complex_vector input = initial_input;
    fft(input.begin(), input.size());
  }, 7, 30000);

  PROFILE_SAVE("test_profile.prof")
}