/*
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// 
//                        Kokkos v. 2.0
//              Copyright (2014) Sandia Corporation
// 
// Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation,
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#include <Kokkos_Core.hpp>
#include <impl/Kokkos_Timer.hpp>
#include <cstdio>
#include <cstdlib>

typedef Kokkos::View<double*> view_type;
// Kokkos::Views have an MemoryTraits template parameter which
// allows users to specify usage scenarios of a View.
// Some of those act simply as hints, which can be used to insert
// optimal load and store paths, others change the symantics of the
// access. The trait Kokkos::Atomic is one of the latter. A view with
// that MemoryTrait will perform any access atomicly (read, write, update).
//
// In this example we use a view with a usage hint for RandomAccess.
// Kokkos::RandomAccess means that we expect to use this view
// with indirect indexing.
//
// In CUDA, RandomAccess allows accesses through the texture
// cache.  This only works if the View is read-only, which we enforce
// through the first template parameter.
//
// Note that we are still talking about views of the data, its not a new allocation.
// For example you can have an atomic view of a default view. While you even
// could use both in the same kernel, this could lead to undefined behaviour because
// one of your access paths is not atomic. Think of it in the same way as you think of
// pointers to const data and pointers to non-const data (i.e. const double* and double*).
// While these pointers can point to the same data you should not use them together if that
// brakes the const guarantee of the first pointer.
typedef Kokkos::View<const double*, Kokkos::MemoryTraits<Kokkos::RandomAccess> > view_type_rnd;
typedef Kokkos::View<int**> idx_type;
typedef idx_type::HostMirror idx_type_host;

// We template this functor on the ViewTypes to show the effect of the RandomAccess trait.
template<class DestType, class SrcType>
struct localsum {
  idx_type::const_type idx;
  DestType dest;
  SrcType src;
  localsum (idx_type idx_, DestType dest_, SrcType src_) :
    idx (idx_), dest (dest_), src (src_)
  {}

  // Calculate a local sum of values
  KOKKOS_INLINE_FUNCTION
  void operator() (const int i) const {
    double tmp = 0.0;
    for (int j = 0; j < (int) idx.extent(1); ++j) {
      // This is an indirect access on src
      const double val = src(idx(i,j));
      tmp += val*val + 0.5*(idx.extent(0)*val -idx.extent(1)*val);
    }
    dest(i) = tmp;
  }
};

int main(int narg, char* arg[]) {
  Kokkos::initialize (narg, arg);

  {
    int size = 1000000;

    idx_type idx("Idx",size,64);
    idx_type_host h_idx = Kokkos::create_mirror_view (idx);

    view_type dest ("Dest", size);
    view_type src ("Src", size);

    srand(134231);

    for (int i = 0; i < size; i++) {
      for (view_type::size_type j = 0; j < h_idx.extent(1); ++j) {
        h_idx(i,j) = (size + i + (rand () % 500 - 250)) % size;
      }
    }

    // Deep copy the initial data to the device
    Kokkos::deep_copy(idx,h_idx);
    // Run the first kernel to warmup caches
    Kokkos::parallel_for(size,localsum<view_type,view_type_rnd>(idx,dest,src));
    Kokkos::fence();

    // Run the localsum functor using the RandomAccess trait. On CPUs there should
    // not be any different in performance to not using the RandomAccess trait.
    // On GPUs where can be a dramatic difference
    Kokkos::Timer time1;
    Kokkos::parallel_for(size,localsum<view_type,view_type_rnd>(idx,dest,src));
    Kokkos::fence();
    double sec1 = time1.seconds();

    Kokkos::Timer time2;
    Kokkos::parallel_for(size,localsum<view_type,view_type>(idx,dest,src));
    Kokkos::fence();
    double sec2 = time2.seconds();

    printf("Time with Trait RandomAccess: %f with Plain: %f \n",sec1,sec2);
  }

  Kokkos::finalize();
}

