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memory_traits.cpp
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memory_traits.cpp
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/*
//@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>
#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.dimension_1 (); ++j) {
// This is an indirect access on src
const double val = src(idx(i,j));
tmp += val*val + 0.5*(idx.dimension_0()*val -idx.dimension_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.dimension_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();
}

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