conjugate_gradient.cc File Reference

#include "sopt/conjugate_gradient.h"
#include <sstream>
#include <benchmark/benchmark.h>

Include dependency graph for conjugate_gradient.cc:

Go to the source code of this file.

Functions
template<typename TYPE >
void	matrix_cg (benchmark::State &state)
template<typename TYPE >
void	function_cg (benchmark::State &state)
	BENCHMARK_TEMPLATE (matrix_cg, sopt::t_complex) -> RangePair(1, 256, 4, 12) ->UseRealTime()
	BENCHMARK_TEMPLATE (matrix_cg, sopt::t_real) -> RangePair(1, 256, 4, 12) ->UseRealTime()
	BENCHMARK_TEMPLATE (function_cg, sopt::t_complex) -> RangePair(1, 256, 4, 12) ->UseRealTime()
	BENCHMARK_TEMPLATE (function_cg, sopt::t_real) -> RangePair(1, 256, 4, 12) ->UseRealTime()
	BENCHMARK_MAIN ()

Function Documentation

BENCHMARK_MAIN()

BENCHMARK_MAIN

(

)

BENCHMARK_TEMPLATE() [1/4]

BENCHMARK_TEMPLATE	(	function_cg	,
		sopt::t_complex
	)		-> RangePair(1, 256, 4, 12) ->UseRealTime()

BENCHMARK_TEMPLATE() [2/4]

BENCHMARK_TEMPLATE	(	function_cg	,
		sopt::t_real
	)		-> RangePair(1, 256, 4, 12) ->UseRealTime()

BENCHMARK_TEMPLATE() [3/4]

BENCHMARK_TEMPLATE	(	matrix_cg	,
		sopt::t_complex
	)		-> RangePair(1, 256, 4, 12) ->UseRealTime()

BENCHMARK_TEMPLATE() [4/4]

BENCHMARK_TEMPLATE	(	matrix_cg	,
		sopt::t_real
	)		-> RangePair(1, 256, 4, 12) ->UseRealTime()

function_cg()

template<typename TYPE >

void function_cg

(

benchmark::State &

state

)

Definition at line 21 of file conjugate_gradient.cc.

                                        {
  auto const N = state.range_x();
  auto const epsilon = std::pow(10, -state.range_y());
  auto const A = sopt::Image<TYPE>::Random(N, N).eval();
  auto const b = sopt::Array<TYPE>::Random(N).eval();
 
  auto const AhA = A.matrix().transpose().conjugate() * A.matrix();
  auto const Ahb = A.matrix().transpose().conjugate() * b.matrix();
  using t_Vector = sopt::Vector<TYPE>;
  auto func = [&AhA](t_Vector &out, t_Vector const &input) { out = AhA * input; };
  auto output = sopt::Vector<TYPE>::Zero(N).eval();
  sopt::ConjugateGradient cg(0, epsilon);
  while (state.KeepRunning()) cg(output, func, Ahb);
  state.SetBytesProcessed(int64_t(state.iterations()) * int64_t(N) * sizeof(TYPE));
}

References b, sopt::epsilon(), and N.

matrix_cg()

template<typename TYPE >

void matrix_cg

(

benchmark::State &

state

)

Definition at line 6 of file conjugate_gradient.cc.

                                      {
  auto const N = state.range_x();
  auto const epsilon = std::pow(10, -state.range_y());
  auto const A = sopt::Image<TYPE>::Random(N, N).eval();
  auto const b = sopt::Array<TYPE>::Random(N).eval();
 
  auto const AhA = A.matrix().transpose().conjugate() * A.matrix();
  auto const Ahb = A.matrix().transpose().conjugate() * b.matrix();
  auto output = sopt::Vector<TYPE>::Zero(N).eval();
  sopt::ConjugateGradient cg(0, epsilon);
  while (state.KeepRunning()) cg(output, AhA, Ahb);
  state.SetBytesProcessed(int64_t(state.iterations()) * int64_t(N) * sizeof(TYPE));
}

References b, sopt::epsilon(), and N.