/*
//@HEADER
// ************************************************************************
//
//                        Kokkos v. 2.0
//              Copyright (2014) Sandia Corporation
//
// Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation,
// the U.S. Government retains certain rights in this software.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are
// met:
//
// 1. Redistributions of source code must retain the above copyright
// notice, this list of conditions and the following disclaimer.
//
// 2. Redistributions in binary form must reproduce the above copyright
// notice, this list of conditions and the following disclaimer in the
// documentation and/or other materials provided with the distribution.
//
// 3. Neither the name of the Corporation nor the names of the
// contributors may be used to endorse or promote products derived from
// this software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY SANDIA CORPORATION "AS IS" AND ANY
// EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL SANDIA CORPORATION OR THE
// CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
// EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
// PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
// PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
// LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
// NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
//
// Questions? Contact  H. Carter Edwards (hcedwar@sandia.gov)
//
// ************************************************************************
//@HEADER
*/

#include <Kokkos_Core.hpp>

template < class ViewType >
struct ParallelScanFunctor {
  using value_type = double;
  ViewType v;

  ParallelScanFunctor( const ViewType & v_ )
    : v(v_)
  {}

  KOKKOS_INLINE_FUNCTION
    void operator()( const int idx, value_type& val, const bool& final ) const
    {
      // inclusive scan
      val += v(idx);
      if ( final ) {
        v(idx) = val;
      }
    }
};

template<class ScheduleType,class IndexType,class ViewType1, class ViewType2, class ViewType3>
void test_policy(int team_range, int thread_range, int vector_range,
          int outer_repeat, int thread_repeat, int inner_repeat,
          int team_size, int vector_size, int test_type,
          ViewType1 &v1, ViewType2 &v2, ViewType3 &v3,
          double &result, double &result_expect, double &time) {
  
  typedef Kokkos::TeamPolicy<ScheduleType,IndexType> t_policy;
  typedef typename t_policy::member_type t_team;
  Kokkos::Timer timer;
  
  for(int orep = 0; orep<outer_repeat; orep++) {

    if (test_type == 100) {
      Kokkos::parallel_for("100 outer for", t_policy(team_range,team_size),
        KOKKOS_LAMBDA (const t_team& team) {
          long idx = team.league_rank()*team.team_size() + team.team_rank();
          v1(idx) = idx;
          // prevent compiler optimizing loop away
      });
    }

    if (test_type == 110) {
      Kokkos::parallel_for("110 outer for", t_policy(team_range,team_size),
        KOKKOS_LAMBDA (const t_team& team) {
          long idx = team.league_rank()*team.team_size() + team.team_rank();
          for (int tr = 0; tr<thread_repeat; ++tr) {
            // Each team launches a parallel_for; thread_range is partitioned among team members
            Kokkos::parallel_for(Kokkos::TeamThreadRange(team,thread_range), [&] (const int t) {
              v2( idx, t ) = t;
              // prevent compiler optimizing loop away
            });
          }             
      });
    }
    if (test_type == 111) {
      Kokkos::parallel_for("111 outer for", t_policy(team_range,team_size,vector_size),
        KOKKOS_LAMBDA (const t_team& team) {
          long idx = team.league_rank()*team.team_size() + team.team_rank();
          for (int tr = 0; tr<thread_repeat; ++tr) {
            // Each team launches a parallel_for; thread_range is partitioned among team members
            Kokkos::parallel_for(Kokkos::TeamThreadRange(team,thread_range), [&] (const int t) {
              for (int vr = 0; vr<inner_repeat; ++vr)
                Kokkos::parallel_for(Kokkos::ThreadVectorRange(team,vector_range), [&] (const int vi) {
                  v3( idx, t, vi ) = vi;
                  // prevent compiler optimizing loop away
                });
            });
          }
      });
    }
    if (test_type == 112) {
      Kokkos::parallel_for("112 outer for", t_policy(team_range,team_size,vector_size),
        KOKKOS_LAMBDA (const t_team& team) {
          long idx = team.league_rank()*team.team_size() + team.team_rank();
          for (int tr = 0; tr<thread_repeat; ++tr) {
            // Each team launches a parallel_for; thread_range is partitioned among team members
            Kokkos::parallel_for(Kokkos::TeamThreadRange(team,thread_range), [&] (const int t) {
              double vector_result = 0.0;
              for (int vr = 0; vr<inner_repeat; ++vr) {
                vector_result = 0.0;
                Kokkos::parallel_reduce(Kokkos::ThreadVectorRange(team,vector_range), [&] (const int vi, double &vval) {
                  vval += 1;
                }, vector_result);
              }
              v2( idx, t ) = vector_result;
              // prevent compiler optimizing loop away
            });
          }
      });
    }
    if (test_type == 120) {
      Kokkos::parallel_for("120 outer for", t_policy(team_range,team_size),
        KOKKOS_LAMBDA (const t_team& team) {
          long idx = team.league_rank()*team.team_size() + team.team_rank();
          double team_result = 0.0;
          for (int tr = 0; tr<thread_repeat; ++tr) {
            team_result = 0.0;
            Kokkos::parallel_reduce(Kokkos::TeamThreadRange(team,thread_range), [&] (const int t, double &lval) {
              lval += 1;
            }, team_result);
          }
          v1(idx) = team_result;
          // prevent compiler optimizing loop away
      });
    }
    if (test_type == 121) {
      Kokkos::parallel_for("121 outer for", t_policy(team_range,team_size,vector_size),
        KOKKOS_LAMBDA (const t_team& team) {
          long idx = team.league_rank()*team.team_size() + team.team_rank();
          double team_result = 0.0;
          for (int tr = 0; tr<thread_repeat; ++tr) {
            team_result = 0.0;
            Kokkos::parallel_reduce(Kokkos::TeamThreadRange(team,thread_range), [&] (const int t, double &lval) {
              lval += 1;
              for (int vr = 0; vr<inner_repeat; ++vr) {
                Kokkos::parallel_for(Kokkos::ThreadVectorRange(team,vector_range), [&] (const int vi) {
                  v3( idx, t, vi ) = vi;
                  // prevent compiler optimizing loop away
                });
              }
            }, team_result);
          }
          v3( idx, 0, 0 ) = team_result;
          // prevent compiler optimizing loop away
      });
    }
    if (test_type == 122) {
      Kokkos::parallel_for("122 outer for", t_policy(team_range,team_size,vector_size),
        KOKKOS_LAMBDA (const t_team& team) {
          long idx = team.league_rank()*team.team_size() + team.team_rank();
          double team_result = 0.0;
          for (int tr = 0; tr<thread_repeat; ++tr) {
            Kokkos::parallel_reduce(Kokkos::TeamThreadRange(team,thread_range), [&] (const int t, double &lval) {
              double vector_result = 0.0;
              for (int vr = 0; vr<inner_repeat; ++vr)
                vector_result = 0.0;
                Kokkos::parallel_reduce(Kokkos::ThreadVectorRange(team,vector_range), [&] (const int vi, double &vval) {
                  vval += 1;
                }, vector_result);
                lval += vector_result;
            }, team_result);
          }
          v1(idx) = team_result;
          // prevent compiler optimizing loop away
      });
    }
    if (test_type == 200) {
      Kokkos::parallel_reduce("200 outer reduce", t_policy(team_range,team_size),                        
        KOKKOS_LAMBDA (const t_team& team, double& lval) {
          lval+=team.team_size()*team.league_rank() + team.team_rank();
      },result);
      result_expect = 0.5* (team_range*team_size)*(team_range*team_size-1);
      // sum ( seq( [0, team_range*team_size) )
    }
    if (test_type == 210) {
      Kokkos::parallel_reduce("210 outer reduce", t_policy(team_range,team_size),
        KOKKOS_LAMBDA (const t_team& team, double& lval) {
        long idx = team.league_rank()*team.team_size() + team.team_rank();
        double thread_for = 1.0;
        for(int tr = 0; tr<thread_repeat; tr++) {
          Kokkos::parallel_for(Kokkos::TeamThreadRange(team,thread_range), [&] (const int t) {
            v2(idx,t) = t;
            // prevent compiler optimizing loop away
          });
        }
        lval+=(team.team_size()*team.league_rank() + team.team_rank() + thread_for);
      },result);
      result_expect = 0.5* (team_range*team_size)*(team_range*team_size-1) + (team_range*team_size);
      // sum ( seq( [0, team_range*team_size) + 1 per team_member (total of team_range*team_size) )
    }
    if (test_type == 211) {
      Kokkos::parallel_reduce("211 outer reduce", t_policy(team_range,team_size,vector_size),
        KOKKOS_LAMBDA (const t_team& team, double& lval) {
        long idx = team.league_rank()*team.team_size() + team.team_rank();
        double thread_for = 1.0;
        for(int tr = 0; tr<thread_repeat; tr++) {
          Kokkos::parallel_for(Kokkos::TeamThreadRange(team,thread_range), [&] (const int t) {
            for (int vr = 0; vr<inner_repeat; ++vr)
              Kokkos::parallel_for(Kokkos::ThreadVectorRange(team, vector_range), [&] (const int vi) {
                v3(idx, t, vi) = vi;
                // prevent compiler optimizing loop away
              });
          });
        }
        lval+=idx+thread_for;
      },result);
      result_expect = 0.5*(team_range*team_size)*(team_range*team_size-1) + (team_range*team_size);
      // sum ( seq( [0, team_range*team_size) + 1 per team_member (total of team_range*team_size) )
    }
    if (test_type == 212) {
      Kokkos::parallel_reduce("212 outer reduce", t_policy(team_range,team_size,vector_size),
        KOKKOS_LAMBDA (const t_team& team, double& lval) {
        long idx = team.league_rank()*team.team_size() + team.team_rank();
        double vector_result = 0.0;
        for(int tr = 0; tr<thread_repeat; tr++) {
          // This parallel_for is executed by each team; the thread_range is partitioned among the team members
          Kokkos::parallel_for(Kokkos::TeamThreadRange(team,thread_range), [&] (const int t) {
            v2(idx,t) = t;
            // prevent compiler optimizing loop away
            for (int vr = 0; vr<inner_repeat; ++vr) {
              vector_result = 0.0;
              Kokkos::parallel_reduce(Kokkos::ThreadVectorRange(team, vector_range), [&] (const int vi, double &vval) {
                vval += vi;
              }, vector_result );
            }
          });
        }
        lval+= idx + vector_result;
      },result);
      result_expect = 0.5*(team_range*team_size)*(team_range*team_size-1) + (0.5*vector_range*(vector_range-1)*team_range*team_size);
      // sum ( seq( [0, team_range*team_size) + sum( seq( [0, vector_range) ) per team_member (total of team_range*team_size) )
    }
    if (test_type == 220) {
      Kokkos::parallel_reduce("220 outer reduce", t_policy(team_range,team_size),
        KOKKOS_LAMBDA (const t_team& team, double& lval) {
        double team_result = 0.0;
        for(int tr = 0; tr<thread_repeat; tr++) {
          Kokkos::parallel_reduce(Kokkos::TeamThreadRange(team,thread_range), [&] (const int t, double& tval) {
            tval += t;
          },team_result);
        }
        lval+=team_result*team.league_rank(); // constant * league_rank
      },result);
      result_expect = 0.5*(team_range)*(team_range-1) * team_size * 0.5*(thread_range)*(thread_range-1);
      // sum ( seq( [0, team_range) * constant ); constant = sum( seq( [0, thread_range) )*team_size (1 per member, result for each team)
    }
    if (test_type == 221) {
      Kokkos::parallel_reduce("221 outer reduce", t_policy(team_range,team_size,vector_size),
        KOKKOS_LAMBDA (const t_team& team, double& lval) {
        long idx = team.league_rank()*team.team_size() + team.team_rank();
        double team_result = 0;
        for(int tr = 0; tr<thread_repeat; tr++) {
          Kokkos::parallel_reduce(Kokkos::TeamThreadRange(team,thread_range), [&] (const int t, double& tval) {
            double vector_for = 1.0;
            for (int vr = 0; vr<inner_repeat; ++vr) {
              Kokkos::parallel_for(Kokkos::ThreadVectorRange(team, vector_range), [&] (const int vi) {
                v3(idx, t, vi) = vi;
                // prevent compiler optimizing loop away
              });
            }
            tval += t + vector_for;
          },team_result);
        }
        lval+=team_result*team.league_rank();
      },result);
      result_expect = 0.5* (team_range)*(team_range-1) * team_size * (0.5*(thread_range) * (thread_range-1) + thread_range);
      // sum ( seq( [0, team_range) * constant ) + 1 per member per team; constant = sum( seq( [0, thread_range) )*team_size (1 per member, result for each team)
    }
    if (test_type == 222) {
      Kokkos::parallel_reduce("222 outer reduce", t_policy(team_range,team_size,vector_size),
        KOKKOS_LAMBDA (const t_team& team, double& lval) {
        double team_result = 0.0;
        for(int tr = 0; tr<thread_repeat; tr++) {
          Kokkos::parallel_reduce(Kokkos::TeamThreadRange(team,thread_range), [&] (const int t, double& tval) {
            double vector_result = 0.0;
            for (int vr = 0; vr<inner_repeat; ++vr) {
              Kokkos::parallel_reduce(Kokkos::ThreadVectorRange(team, vector_range), [&] (const int vi, double& vval) {
                vval += vi;
              }, vector_result);
            }
            tval += t + vector_result;
          },team_result);
        }
        lval+=team_result*team.league_rank();
      },result);
      result_expect = 0.5* (team_range)*(team_range-1) * team_size * (0.5*(thread_range) * (thread_range-1) + thread_range*0.5*(vector_range)*(vector_range-1));
      // sum ( seq( [0, team_range) * constant ) + 1 + sum( seq([0,vector_range) ) per member per team; constant = sum( seq( [0, thread_range) )*team_size (1 per member, result for each team)
    }

    // parallel_for RangePolicy: range = team_size*team_range
    if (test_type == 300) {
      Kokkos::parallel_for("300 outer for", team_size*team_range, 
        KOKKOS_LAMBDA (const int idx) {
          v1(idx) = idx;
          // prevent compiler from optimizing away the loop
      });
    }
    // parallel_reduce RangePolicy: range = team_size*team_range
    if (test_type == 400) {
      Kokkos::parallel_reduce("400 outer reduce", team_size*team_range, 
        KOKKOS_LAMBDA (const int idx, double& val) {
          val += idx;
      }, result);
      result_expect = 0.5*(team_size*team_range)*(team_size*team_range-1);
    }
    // parallel_scan RangePolicy: range = team_size*team_range
    if (test_type == 500) {
      Kokkos::parallel_scan("500 outer scan", team_size*team_range, 
        ParallelScanFunctor<ViewType1>(v1)
#if 0
        // This does not compile with pre Cuda 8.0 - see Github Issue #913 for explanation
        KOKKOS_LAMBDA (const int idx, double& val, const bool& final) {
          // inclusive scan
          val += v1(idx);
          if ( final ) {
            v1(idx) = val;
          }
        }
#endif
      );
      // result = v1( team_size*team_range - 1 ); // won't work with Cuda - need to copy result back to host to print
      // result_expect = 0.5*(team_size*team_range)*(team_size*team_range-1);
    }

  } // end outer for loop

  time = timer.seconds();
} //end test_policy
