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lammps/lib/kokkos/core/unit_test/TestReduce.hpp
2017-04-25 13:48:51 -06:00

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/*
//@HEADER
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//
// Kokkos v. 2.0
// Copyright (2014) Sandia Corporation
//
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//
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// 2. Redistributions in binary form must reproduce the above copyright
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// 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.
//
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// EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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#include <stdexcept>
#include <sstream>
#include <iostream>
#include <limits>
#include <Kokkos_Core.hpp>
namespace Test {
template< typename ScalarType, class DeviceType >
class ReduceFunctor
{
public:
typedef DeviceType execution_space;
typedef typename execution_space::size_type size_type;
struct value_type {
ScalarType value[3];
};
const size_type nwork;
ReduceFunctor( const size_type & arg_nwork )
: nwork( arg_nwork ) {}
ReduceFunctor( const ReduceFunctor & rhs )
: nwork( rhs.nwork ) {}
/*
KOKKOS_INLINE_FUNCTION
void init( value_type & dst ) const
{
dst.value[0] = 0;
dst.value[1] = 0;
dst.value[2] = 0;
}
*/
KOKKOS_INLINE_FUNCTION
void join( volatile value_type & dst,
const volatile value_type & src ) const
{
dst.value[0] += src.value[0];
dst.value[1] += src.value[1];
dst.value[2] += src.value[2];
}
KOKKOS_INLINE_FUNCTION
void operator()( size_type iwork, value_type & dst ) const
{
dst.value[0] += 1;
dst.value[1] += iwork + 1;
dst.value[2] += nwork - iwork;
}
};
template< class DeviceType >
class ReduceFunctorFinal : public ReduceFunctor< long, DeviceType > {
public:
typedef typename ReduceFunctor< long, DeviceType >::value_type value_type;
ReduceFunctorFinal( const size_t n )
: ReduceFunctor< long, DeviceType >( n ) {}
KOKKOS_INLINE_FUNCTION
void final( value_type & dst ) const
{
dst.value[0] = -dst.value[0];
dst.value[1] = -dst.value[1];
dst.value[2] = -dst.value[2];
}
};
template< typename ScalarType, class DeviceType >
class RuntimeReduceFunctor
{
public:
// Required for functor:
typedef DeviceType execution_space;
typedef ScalarType value_type[];
const unsigned value_count;
// Unit test details:
typedef typename execution_space::size_type size_type;
const size_type nwork;
RuntimeReduceFunctor( const size_type arg_nwork,
const size_type arg_count )
: value_count( arg_count )
, nwork( arg_nwork ) {}
KOKKOS_INLINE_FUNCTION
void init( ScalarType dst[] ) const
{
for ( unsigned i = 0; i < value_count; ++i ) dst[i] = 0;
}
KOKKOS_INLINE_FUNCTION
void join( volatile ScalarType dst[],
const volatile ScalarType src[] ) const
{
for ( unsigned i = 0; i < value_count; ++i ) dst[i] += src[i];
}
KOKKOS_INLINE_FUNCTION
void operator()( size_type iwork, ScalarType dst[] ) const
{
const size_type tmp[3] = { 1, iwork + 1, nwork - iwork };
for ( size_type i = 0; i < value_count; ++i ) {
dst[i] += tmp[ i % 3 ];
}
}
};
template< typename ScalarType, class DeviceType >
class RuntimeReduceMinMax
{
public:
// Required for functor:
typedef DeviceType execution_space;
typedef ScalarType value_type[];
const unsigned value_count;
// Unit test details:
typedef typename execution_space::size_type size_type;
const size_type nwork;
const ScalarType amin;
const ScalarType amax;
RuntimeReduceMinMax( const size_type arg_nwork,
const size_type arg_count )
: value_count( arg_count )
, nwork( arg_nwork )
, amin( std::numeric_limits< ScalarType >::min() )
, amax( std::numeric_limits< ScalarType >::max() )
{}
KOKKOS_INLINE_FUNCTION
void init( ScalarType dst[] ) const
{
for ( unsigned i = 0; i < value_count; ++i ) {
dst[i] = i % 2 ? amax : amin;
}
}
KOKKOS_INLINE_FUNCTION
void join( volatile ScalarType dst[],
const volatile ScalarType src[] ) const
{
for ( unsigned i = 0; i < value_count; ++i ) {
dst[i] = i % 2 ? ( dst[i] < src[i] ? dst[i] : src[i] ) // min
: ( dst[i] > src[i] ? dst[i] : src[i] ); // max
}
}
KOKKOS_INLINE_FUNCTION
void operator()( size_type iwork, ScalarType dst[] ) const
{
const ScalarType tmp[2] = { ScalarType( iwork + 1 )
, ScalarType( nwork - iwork ) };
for ( size_type i = 0; i < value_count; ++i ) {
dst[i] = i % 2 ? ( dst[i] < tmp[i % 2] ? dst[i] : tmp[i % 2] )
: ( dst[i] > tmp[i % 2] ? dst[i] : tmp[i % 2] );
}
}
};
template< class DeviceType >
class RuntimeReduceFunctorFinal : public RuntimeReduceFunctor< long, DeviceType > {
public:
typedef RuntimeReduceFunctor< long, DeviceType > base_type;
typedef typename base_type::value_type value_type;
typedef long scalar_type;
RuntimeReduceFunctorFinal( const size_t theNwork, const size_t count )
: base_type( theNwork, count ) {}
KOKKOS_INLINE_FUNCTION
void final( value_type dst ) const
{
for ( unsigned i = 0; i < base_type::value_count; ++i ) {
dst[i] = -dst[i];
}
}
};
} // namespace Test
namespace {
template< typename ScalarType, class DeviceType >
class TestReduce
{
public:
typedef DeviceType execution_space;
typedef typename execution_space::size_type size_type;
TestReduce( const size_type & nwork )
{
run_test( nwork );
run_test_final( nwork );
}
void run_test( const size_type & nwork )
{
typedef Test::ReduceFunctor< ScalarType, execution_space > functor_type;
typedef typename functor_type::value_type value_type;
enum { Count = 3 };
enum { Repeat = 100 };
value_type result[ Repeat ];
const unsigned long nw = nwork;
const unsigned long nsum = nw % 2 ? nw * ( ( nw + 1 ) / 2 )
: ( nw / 2 ) * ( nw + 1 );
for ( unsigned i = 0; i < Repeat; ++i ) {
Kokkos::parallel_reduce( nwork, functor_type( nwork ), result[i] );
}
for ( unsigned i = 0; i < Repeat; ++i ) {
for ( unsigned j = 0; j < Count; ++j ) {
const unsigned long correct = 0 == j % 3 ? nw : nsum;
ASSERT_EQ( (ScalarType) correct, result[i].value[j] );
}
}
}
void run_test_final( const size_type & nwork )
{
typedef Test::ReduceFunctorFinal< execution_space > functor_type;
typedef typename functor_type::value_type value_type;
enum { Count = 3 };
enum { Repeat = 100 };
value_type result[ Repeat ];
const unsigned long nw = nwork;
const unsigned long nsum = nw % 2 ? nw * ( ( nw + 1 ) / 2 )
: ( nw / 2 ) * ( nw + 1 );
for ( unsigned i = 0; i < Repeat; ++i ) {
if ( i % 2 == 0 ) {
Kokkos::parallel_reduce( nwork, functor_type( nwork ), result[i] );
}
else {
Kokkos::parallel_reduce( "Reduce", nwork, functor_type( nwork ), result[i] );
}
}
for ( unsigned i = 0; i < Repeat; ++i ) {
for ( unsigned j = 0; j < Count; ++j ) {
const unsigned long correct = 0 == j % 3 ? nw : nsum;
ASSERT_EQ( (ScalarType) correct, -result[i].value[j] );
}
}
}
};
template< typename ScalarType, class DeviceType >
class TestReduceDynamic
{
public:
typedef DeviceType execution_space;
typedef typename execution_space::size_type size_type;
TestReduceDynamic( const size_type nwork )
{
run_test_dynamic( nwork );
run_test_dynamic_minmax( nwork );
run_test_dynamic_final( nwork );
}
void run_test_dynamic( const size_type nwork )
{
typedef Test::RuntimeReduceFunctor< ScalarType, execution_space > functor_type;
enum { Count = 3 };
enum { Repeat = 100 };
ScalarType result[ Repeat ][ Count ];
const unsigned long nw = nwork;
const unsigned long nsum = nw % 2 ? nw * ( ( nw + 1 ) / 2 )
: ( nw / 2 ) * ( nw + 1 );
for ( unsigned i = 0; i < Repeat; ++i ) {
if ( i % 2 == 0 ) {
Kokkos::parallel_reduce( nwork, functor_type( nwork, Count ), result[i] );
}
else {
Kokkos::parallel_reduce( "Reduce", nwork, functor_type( nwork, Count ), result[i] );
}
}
for ( unsigned i = 0; i < Repeat; ++i ) {
for ( unsigned j = 0; j < Count; ++j ) {
const unsigned long correct = 0 == j % 3 ? nw : nsum;
ASSERT_EQ( (ScalarType) correct, result[i][j] );
}
}
}
void run_test_dynamic_minmax( const size_type nwork )
{
typedef Test::RuntimeReduceMinMax< ScalarType, execution_space > functor_type;
enum { Count = 2 };
enum { Repeat = 100 };
ScalarType result[ Repeat ][ Count ];
for ( unsigned i = 0; i < Repeat; ++i ) {
if ( i % 2 == 0 ) {
Kokkos::parallel_reduce( nwork, functor_type( nwork, Count ), result[i] );
}
else {
Kokkos::parallel_reduce( "Reduce", nwork, functor_type( nwork, Count ), result[i] );
}
}
for ( unsigned i = 0; i < Repeat; ++i ) {
for ( unsigned j = 0; j < Count; ++j ) {
if ( nwork == 0 )
{
ScalarType amin( std::numeric_limits< ScalarType >::min() );
ScalarType amax( std::numeric_limits< ScalarType >::max() );
const ScalarType correct = ( j % 2 ) ? amax : amin;
ASSERT_EQ( (ScalarType) correct, result[i][j] );
}
else {
const unsigned long correct = j % 2 ? 1 : nwork;
ASSERT_EQ( (ScalarType) correct, result[i][j] );
}
}
}
}
void run_test_dynamic_final( const size_type nwork )
{
typedef Test::RuntimeReduceFunctorFinal< execution_space > functor_type;
enum { Count = 3 };
enum { Repeat = 100 };
typename functor_type::scalar_type result[ Repeat ][ Count ];
const unsigned long nw = nwork;
const unsigned long nsum = nw % 2 ? nw * ( ( nw + 1 ) / 2 )
: ( nw / 2 ) * ( nw + 1 );
for ( unsigned i = 0; i < Repeat; ++i ) {
if ( i % 2 == 0 ) {
Kokkos::parallel_reduce( nwork, functor_type( nwork, Count ), result[i] );
}
else {
Kokkos::parallel_reduce( "TestKernelReduce", nwork, functor_type( nwork, Count ), result[i] );
}
}
for ( unsigned i = 0; i < Repeat; ++i ) {
for ( unsigned j = 0; j < Count; ++j ) {
const unsigned long correct = 0 == j % 3 ? nw : nsum;
ASSERT_EQ( (ScalarType) correct, -result[i][j] );
}
}
}
};
template< typename ScalarType, class DeviceType >
class TestReduceDynamicView
{
public:
typedef DeviceType execution_space;
typedef typename execution_space::size_type size_type;
TestReduceDynamicView( const size_type nwork )
{
run_test_dynamic_view( nwork );
}
void run_test_dynamic_view( const size_type nwork )
{
typedef Test::RuntimeReduceFunctor< ScalarType, execution_space > functor_type;
typedef Kokkos::View< ScalarType*, DeviceType > result_type;
typedef typename result_type::HostMirror result_host_type;
const unsigned CountLimit = 23;
const unsigned long nw = nwork;
const unsigned long nsum = nw % 2 ? nw * ( ( nw + 1 ) / 2 )
: ( nw / 2 ) * ( nw + 1 );
for ( unsigned count = 0; count < CountLimit; ++count ) {
result_type result( "result", count );
result_host_type host_result = Kokkos::create_mirror( result );
// Test result to host pointer:
std::string str( "TestKernelReduce" );
if ( count % 2 == 0 ) {
Kokkos::parallel_reduce( nw, functor_type( nw, count ), host_result.ptr_on_device() );
}
else {
Kokkos::parallel_reduce( str, nw, functor_type( nw, count ), host_result.ptr_on_device() );
}
for ( unsigned j = 0; j < count; ++j ) {
const unsigned long correct = 0 == j % 3 ? nw : nsum;
ASSERT_EQ( host_result( j ), (ScalarType) correct );
host_result( j ) = 0;
}
}
}
};
} // namespace
// Computes y^T*A*x
// ( modified from kokkos-tutorials/GTC2016/Exercises/ThreeLevelPar )
#if ( ! defined( KOKKOS_ENABLE_CUDA ) ) || defined( KOKKOS_ENABLE_CUDA_LAMBDA )
template< typename ScalarType, class DeviceType >
class TestTripleNestedReduce
{
public:
typedef DeviceType execution_space;
typedef typename execution_space::size_type size_type;
TestTripleNestedReduce( const size_type & nrows, const size_type & ncols
, const size_type & team_size, const size_type & vector_length )
{
run_test( nrows, ncols, team_size, vector_length );
}
void run_test( const size_type & nrows, const size_type & ncols
, const size_type & team_size, const size_type & vector_length )
{
//typedef Kokkos::LayoutLeft Layout;
typedef Kokkos::LayoutRight Layout;
typedef Kokkos::View< ScalarType*, DeviceType > ViewVector;
typedef Kokkos::View< ScalarType**, Layout, DeviceType > ViewMatrix;
ViewVector y( "y", nrows );
ViewVector x( "x", ncols );
ViewMatrix A( "A", nrows, ncols );
typedef Kokkos::RangePolicy<DeviceType> range_policy;
// Initialize y vector.
Kokkos::parallel_for( range_policy( 0, nrows ), KOKKOS_LAMBDA ( const int i ) { y( i ) = 1; } );
// Initialize x vector.
Kokkos::parallel_for( range_policy( 0, ncols ), KOKKOS_LAMBDA ( const int i ) { x( i ) = 1; } );
typedef Kokkos::TeamPolicy< DeviceType > team_policy;
typedef typename Kokkos::TeamPolicy< DeviceType >::member_type member_type;
// Initialize A matrix, note 2D indexing computation.
Kokkos::parallel_for( team_policy( nrows, Kokkos::AUTO ), KOKKOS_LAMBDA ( const member_type & teamMember ) {
const int j = teamMember.league_rank();
Kokkos::parallel_for( Kokkos::TeamThreadRange( teamMember, ncols ), [&] ( const int i ) {
A( j, i ) = 1;
} );
} );
// Three level parallelism kernel to force caching of vector x.
ScalarType result = 0.0;
int chunk_size = 128;
Kokkos::parallel_reduce( team_policy( nrows / chunk_size, team_size, vector_length ),
KOKKOS_LAMBDA ( const member_type & teamMember, double & update ) {
const int row_start = teamMember.league_rank() * chunk_size;
const int row_end = row_start + chunk_size;
Kokkos::parallel_for( Kokkos::TeamThreadRange( teamMember, row_start, row_end ), [&] ( const int i ) {
ScalarType sum_i = 0.0;
Kokkos::parallel_reduce( Kokkos::ThreadVectorRange( teamMember, ncols ), [&] ( const int j, ScalarType &innerUpdate ) {
innerUpdate += A( i, j ) * x( j );
}, sum_i );
Kokkos::single( Kokkos::PerThread( teamMember ), [&] () {
update += y( i ) * sum_i;
} );
} );
}, result );
const ScalarType solution = (ScalarType) nrows * (ScalarType) ncols;
ASSERT_EQ( solution, result );
}
};
#else // #if ( ! defined( KOKKOS_ENABLE_CUDA ) ) || defined( KOKKOS_ENABLE_CUDA_LAMBDA )
template< typename ScalarType, class DeviceType >
class TestTripleNestedReduce
{
public:
typedef DeviceType execution_space;
typedef typename execution_space::size_type size_type;
TestTripleNestedReduce( const size_type &, const size_type
, const size_type &, const size_type )
{}
};
#endif
//--------------------------------------------------------------------------
namespace Test {
namespace ReduceCombinatorical {
template< class Scalar, class Space = Kokkos::HostSpace >
struct AddPlus {
public:
// Required.
typedef AddPlus reducer_type;
typedef Scalar value_type;
typedef Kokkos::View< value_type, Space, Kokkos::MemoryTraits<Kokkos::Unmanaged> > result_view_type;
private:
result_view_type result;
public:
AddPlus( value_type & result_ ) : result( &result_ ) {}
// Required.
KOKKOS_INLINE_FUNCTION
void join( value_type & dest, const value_type & src ) const {
dest += src + 1;
}
KOKKOS_INLINE_FUNCTION
void join( volatile value_type & dest, const volatile value_type & src ) const {
dest += src + 1;
}
// Optional.
KOKKOS_INLINE_FUNCTION
void init( value_type & val ) const {
val = value_type();
}
result_view_type result_view() const {
return result;
}
};
template< int ISTEAM >
struct FunctorScalar;
template<>
struct FunctorScalar< 0 > {
Kokkos::View< double > result;
FunctorScalar( Kokkos::View< double > r ) : result( r ) {}
KOKKOS_INLINE_FUNCTION
void operator()( const int & i, double & update ) const {
update += i;
}
};
template<>
struct FunctorScalar< 1 > {
typedef Kokkos::TeamPolicy<>::member_type team_type;
Kokkos::View< double > result;
FunctorScalar( Kokkos::View< double > r ) : result( r ) {}
KOKKOS_INLINE_FUNCTION
void operator()( const team_type & team, double & update ) const {
update += 1.0 / team.team_size() * team.league_rank();
}
};
template< int ISTEAM >
struct FunctorScalarInit;
template<>
struct FunctorScalarInit< 0 > {
Kokkos::View< double > result;
FunctorScalarInit( Kokkos::View< double > r ) : result( r ) {}
KOKKOS_INLINE_FUNCTION
void operator()( const int & i, double & update ) const {
update += i;
}
KOKKOS_INLINE_FUNCTION
void init( double & update ) const {
update = 0.0;
}
};
template<>
struct FunctorScalarInit< 1 > {
typedef Kokkos::TeamPolicy<>::member_type team_type;
Kokkos::View< double > result;
FunctorScalarInit( Kokkos::View< double > r ) : result( r ) {}
KOKKOS_INLINE_FUNCTION
void operator()( const team_type & team, double & update ) const {
update += 1.0 / team.team_size() * team.league_rank();
}
KOKKOS_INLINE_FUNCTION
void init( double & update ) const {
update = 0.0;
}
};
template< int ISTEAM >
struct FunctorScalarFinal;
template<>
struct FunctorScalarFinal< 0 > {
Kokkos::View<double> result;
FunctorScalarFinal( Kokkos::View< double > r ) : result( r ) {}
KOKKOS_INLINE_FUNCTION
void operator()( const int & i, double & update ) const {
update += i;
}
KOKKOS_INLINE_FUNCTION
void final( double & update ) const {
result() = update;
}
};
template<>
struct FunctorScalarFinal< 1 > {
typedef Kokkos::TeamPolicy<>::member_type team_type;
Kokkos::View< double > result;
FunctorScalarFinal( Kokkos::View< double > r ) : result( r ) {}
KOKKOS_INLINE_FUNCTION
void operator()( const team_type & team, double & update ) const {
update += 1.0 / team.team_size() * team.league_rank();
}
KOKKOS_INLINE_FUNCTION
void final( double & update ) const {
result() = update;
}
};
template< int ISTEAM >
struct FunctorScalarJoin;
template<>
struct FunctorScalarJoin< 0 > {
Kokkos::View<double> result;
FunctorScalarJoin( Kokkos::View< double > r ) : result( r ) {}
KOKKOS_INLINE_FUNCTION
void operator()( const int & i, double & update ) const {
update += i;
}
KOKKOS_INLINE_FUNCTION
void join( volatile double & dst, const volatile double & update ) const {
dst += update;
}
};
template<>
struct FunctorScalarJoin< 1 > {
typedef Kokkos::TeamPolicy<>::member_type team_type;
Kokkos::View< double > result;
FunctorScalarJoin( Kokkos::View< double > r ) : result( r ) {}
KOKKOS_INLINE_FUNCTION
void operator()( const team_type & team, double & update ) const {
update += 1.0 / team.team_size() * team.league_rank();
}
KOKKOS_INLINE_FUNCTION
void join( volatile double & dst, const volatile double & update ) const {
dst += update;
}
};
template< int ISTEAM >
struct FunctorScalarJoinFinal;
template<>
struct FunctorScalarJoinFinal< 0 > {
Kokkos::View< double > result;
FunctorScalarJoinFinal( Kokkos::View< double > r ) : result( r ) {}
KOKKOS_INLINE_FUNCTION
void operator()( const int & i, double & update ) const {
update += i;
}
KOKKOS_INLINE_FUNCTION
void join( volatile double & dst, const volatile double & update ) const {
dst += update;
}
KOKKOS_INLINE_FUNCTION
void final( double & update ) const {
result() = update;
}
};
template<>
struct FunctorScalarJoinFinal< 1 > {
typedef Kokkos::TeamPolicy<>::member_type team_type;
Kokkos::View< double > result;
FunctorScalarJoinFinal( Kokkos::View< double > r ) : result( r ) {}
KOKKOS_INLINE_FUNCTION
void operator()( const team_type & team, double & update ) const {
update += 1.0 / team.team_size() * team.league_rank();
}
KOKKOS_INLINE_FUNCTION
void join( volatile double & dst, const volatile double & update ) const {
dst += update;
}
KOKKOS_INLINE_FUNCTION
void final( double & update ) const {
result() = update;
}
};
template< int ISTEAM >
struct FunctorScalarJoinInit;
template<>
struct FunctorScalarJoinInit< 0 > {
Kokkos::View< double > result;
FunctorScalarJoinInit( Kokkos::View< double > r ) : result( r ) {}
KOKKOS_INLINE_FUNCTION
void operator()( const int & i, double & update ) const {
update += i;
}
KOKKOS_INLINE_FUNCTION
void join( volatile double & dst, const volatile double & update ) const {
dst += update;
}
KOKKOS_INLINE_FUNCTION
void init( double & update ) const {
update = 0.0;
}
};
template<>
struct FunctorScalarJoinInit< 1 > {
typedef Kokkos::TeamPolicy<>::member_type team_type;
Kokkos::View< double > result;
FunctorScalarJoinInit( Kokkos::View< double > r ) : result( r ) {}
KOKKOS_INLINE_FUNCTION
void operator()( const team_type & team, double & update ) const {
update += 1.0 / team.team_size() * team.league_rank();
}
KOKKOS_INLINE_FUNCTION
void join( volatile double & dst, const volatile double & update ) const {
dst += update;
}
KOKKOS_INLINE_FUNCTION
void init( double & update ) const {
update = 0.0;
}
};
template< int ISTEAM >
struct FunctorScalarJoinFinalInit;
template<>
struct FunctorScalarJoinFinalInit< 0 > {
Kokkos::View<double> result;
FunctorScalarJoinFinalInit( Kokkos::View< double > r ) : result( r ) {}
KOKKOS_INLINE_FUNCTION
void operator()( const int & i, double & update ) const {
update += i;
}
KOKKOS_INLINE_FUNCTION
void join( volatile double & dst, const volatile double & update ) const {
dst += update;
}
KOKKOS_INLINE_FUNCTION
void final( double & update ) const {
result() = update;
}
KOKKOS_INLINE_FUNCTION
void init( double & update ) const {
update = 0.0;
}
};
template<>
struct FunctorScalarJoinFinalInit< 1 > {
typedef Kokkos::TeamPolicy<>::member_type team_type;
Kokkos::View< double > result;
FunctorScalarJoinFinalInit( Kokkos::View< double > r ) : result( r ) {}
KOKKOS_INLINE_FUNCTION
void operator()( const team_type & team, double & update ) const {
update += 1.0 / team.team_size() * team.league_rank();
}
KOKKOS_INLINE_FUNCTION
void join( volatile double & dst, const volatile double & update ) const {
dst += update;
}
KOKKOS_INLINE_FUNCTION
void final( double & update ) const {
result() = update;
}
KOKKOS_INLINE_FUNCTION
void init( double & update ) const {
update = 0.0;
}
};
struct Functor1 {
KOKKOS_INLINE_FUNCTION
void operator()( const int & i, double & update ) const {
update += i;
}
};
struct Functor2 {
typedef double value_type[];
const unsigned value_count;
Functor2( unsigned n ) : value_count( n ) {}
KOKKOS_INLINE_FUNCTION
void operator()( const unsigned & i, double update[] ) const {
for ( unsigned j = 0; j < value_count; j++ ) {
update[j] += i;
}
}
KOKKOS_INLINE_FUNCTION
void init( double dst[] ) const
{
for ( unsigned i = 0; i < value_count; ++i ) dst[i] = 0;
}
KOKKOS_INLINE_FUNCTION
void join( volatile double dst[],
const volatile double src[] ) const
{
for ( unsigned i = 0; i < value_count; ++i ) dst[i] += src[i];
}
};
} // namespace ReduceCombinatorical
} // namespace Test
namespace Test {
template< class ExecSpace = Kokkos::DefaultExecutionSpace >
struct TestReduceCombinatoricalInstantiation {
template< class ... Args >
static void CallParallelReduce( Args... args ) {
Kokkos::parallel_reduce( args... );
}
template< class ... Args >
static void AddReturnArgument( Args... args ) {
Kokkos::View< double, Kokkos::HostSpace > result_view( "ResultView" );
double expected_result = 1000.0 * 999.0 / 2.0;
double value = 0;
Kokkos::parallel_reduce( args..., value );
ASSERT_EQ( expected_result, value );
result_view() = 0;
CallParallelReduce( args..., result_view );
ASSERT_EQ( expected_result, result_view() );
value = 0;
CallParallelReduce( args..., Kokkos::View< double, Kokkos::HostSpace, Kokkos::MemoryTraits<Kokkos::Unmanaged> >( &value ) );
ASSERT_EQ( expected_result, value );
result_view() = 0;
const Kokkos::View< double, Kokkos::HostSpace, Kokkos::MemoryTraits<Kokkos::Unmanaged> > result_view_const_um = result_view;
CallParallelReduce( args..., result_view_const_um );
ASSERT_EQ( expected_result, result_view_const_um() );
value = 0;
CallParallelReduce( args..., Test::ReduceCombinatorical::AddPlus< double >( value ) );
if ( ( Kokkos::DefaultExecutionSpace::concurrency() > 1 ) && ( ExecSpace::concurrency() > 1 ) ) {
ASSERT_TRUE( expected_result < value );
}
else if ( ( Kokkos::DefaultExecutionSpace::concurrency() > 1 ) || ( ExecSpace::concurrency() > 1 ) ) {
ASSERT_TRUE( expected_result <= value );
}
else {
ASSERT_EQ( expected_result, value );
}
value = 0;
Test::ReduceCombinatorical::AddPlus< double > add( value );
CallParallelReduce( args..., add );
if ( ( Kokkos::DefaultExecutionSpace::concurrency() > 1 ) && ( ExecSpace::concurrency() > 1 ) ) {
ASSERT_TRUE( expected_result < value );
}
else if ( ( Kokkos::DefaultExecutionSpace::concurrency() > 1 ) || ( ExecSpace::concurrency() > 1 ) ) {
ASSERT_TRUE( expected_result <= value );
}
else {
ASSERT_EQ( expected_result, value );
}
}
template< class ... Args >
static void AddLambdaRange( void*, Args... args ) {
AddReturnArgument( args..., KOKKOS_LAMBDA ( const int & i, double & lsum ) {
lsum += i;
});
}
template< class ... Args >
static void AddLambdaTeam( void*, Args... args ) {
AddReturnArgument( args..., KOKKOS_LAMBDA ( const Kokkos::TeamPolicy<>::member_type & team, double & update ) {
update += 1.0 / team.team_size() * team.league_rank();
});
}
template< class ... Args >
static void AddLambdaRange( Kokkos::InvalidType, Args... args ) {}
template< class ... Args >
static void AddLambdaTeam( Kokkos::InvalidType, Args... args ) {}
template< int ISTEAM, class ... Args >
static void AddFunctor( Args... args ) {
Kokkos::View< double > result_view( "FunctorView" );
auto h_r = Kokkos::create_mirror_view( result_view );
Test::ReduceCombinatorical::FunctorScalar< ISTEAM > functor( result_view );
double expected_result = 1000.0 * 999.0 / 2.0;
AddReturnArgument( args..., functor );
AddReturnArgument( args..., Test::ReduceCombinatorical::FunctorScalar< ISTEAM >( result_view ) );
AddReturnArgument( args..., Test::ReduceCombinatorical::FunctorScalarInit< ISTEAM >( result_view ) );
AddReturnArgument( args..., Test::ReduceCombinatorical::FunctorScalarJoin< ISTEAM >( result_view ) );
AddReturnArgument( args..., Test::ReduceCombinatorical::FunctorScalarJoinInit< ISTEAM >( result_view ) );
h_r() = 0;
Kokkos::deep_copy( result_view, h_r );
CallParallelReduce( args..., Test::ReduceCombinatorical::FunctorScalarFinal< ISTEAM >( result_view ) );
Kokkos::deep_copy( h_r, result_view );
ASSERT_EQ( expected_result, h_r() );
h_r() = 0;
Kokkos::deep_copy( result_view, h_r );
CallParallelReduce( args..., Test::ReduceCombinatorical::FunctorScalarJoinFinal< ISTEAM >( result_view ) );
Kokkos::deep_copy( h_r, result_view );
ASSERT_EQ( expected_result, h_r() );
h_r() = 0;
Kokkos::deep_copy( result_view, h_r );
CallParallelReduce( args..., Test::ReduceCombinatorical::FunctorScalarJoinFinalInit< ISTEAM >( result_view ) );
Kokkos::deep_copy( h_r, result_view );
ASSERT_EQ( expected_result, h_r() );
}
template< class ... Args >
static void AddFunctorLambdaRange( Args... args ) {
AddFunctor< 0, Args... >( args... );
#ifdef KOKKOS_ENABLE_CXX11_DISPATCH_LAMBDA
AddLambdaRange( typename std::conditional< std::is_same<ExecSpace, Kokkos::DefaultExecutionSpace>::value, void*, Kokkos::InvalidType >::type(), args... );
#endif
}
template< class ... Args >
static void AddFunctorLambdaTeam( Args... args ) {
AddFunctor< 1, Args... >( args... );
#ifdef KOKKOS_ENABLE_CXX11_DISPATCH_LAMBDA
AddLambdaTeam( typename std::conditional< std::is_same<ExecSpace, Kokkos::DefaultExecutionSpace>::value, void*, Kokkos::InvalidType >::type(), args... );
#endif
}
template< class ... Args >
static void AddPolicy( Args... args ) {
int N = 1000;
Kokkos::RangePolicy< ExecSpace > policy( 0, N );
AddFunctorLambdaRange( args..., 1000 );
AddFunctorLambdaRange( args..., N );
AddFunctorLambdaRange( args..., policy );
AddFunctorLambdaRange( args..., Kokkos::RangePolicy< ExecSpace >( 0, N ) );
AddFunctorLambdaRange( args..., Kokkos::RangePolicy< ExecSpace, Kokkos::Schedule<Kokkos::Dynamic> >( 0, N ) );
AddFunctorLambdaRange( args..., Kokkos::RangePolicy< ExecSpace, Kokkos::Schedule<Kokkos::Static> >( 0, N ).set_chunk_size( 10 ) );
AddFunctorLambdaRange( args..., Kokkos::RangePolicy< ExecSpace, Kokkos::Schedule<Kokkos::Dynamic> >( 0, N ).set_chunk_size( 10 ) );
AddFunctorLambdaTeam( args..., Kokkos::TeamPolicy< ExecSpace >( N, Kokkos::AUTO ) );
AddFunctorLambdaTeam( args..., Kokkos::TeamPolicy< ExecSpace, Kokkos::Schedule<Kokkos::Dynamic> >( N, Kokkos::AUTO ) );
AddFunctorLambdaTeam( args..., Kokkos::TeamPolicy< ExecSpace, Kokkos::Schedule<Kokkos::Static> >( N, Kokkos::AUTO ).set_chunk_size( 10 ) );
AddFunctorLambdaTeam( args..., Kokkos::TeamPolicy< ExecSpace, Kokkos::Schedule<Kokkos::Dynamic> >( N, Kokkos::AUTO ).set_chunk_size( 10 ) );
}
static void execute_a() {
AddPolicy();
}
static void execute_b() {
std::string s( "Std::String" );
AddPolicy( s.c_str() );
AddPolicy( "Char Constant" );
}
static void execute_c() {
std::string s( "Std::String" );
AddPolicy( s );
}
};
template< class Scalar, class ExecSpace = Kokkos::DefaultExecutionSpace >
struct TestReducers {
struct SumFunctor {
Kokkos::View< const Scalar*, ExecSpace > values;
KOKKOS_INLINE_FUNCTION
void operator()( const int & i, Scalar & value ) const {
value += values( i );
}
};
struct ProdFunctor {
Kokkos::View< const Scalar*, ExecSpace > values;
KOKKOS_INLINE_FUNCTION
void operator()( const int & i, Scalar & value ) const {
value *= values( i );
}
};
struct MinFunctor {
Kokkos::View< const Scalar*, ExecSpace > values;
KOKKOS_INLINE_FUNCTION
void operator()( const int & i, Scalar & value ) const {
if ( values( i ) < value ) value = values( i );
}
};
struct MaxFunctor {
Kokkos::View< const Scalar*, ExecSpace > values;
KOKKOS_INLINE_FUNCTION
void operator()( const int & i, Scalar & value ) const {
if ( values( i ) > value ) value = values( i );
}
};
struct MinLocFunctor {
Kokkos::View< const Scalar*, ExecSpace > values;
KOKKOS_INLINE_FUNCTION
void operator()( const int & i, typename Kokkos::Experimental::MinLoc< Scalar, int >::value_type & value ) const {
if ( values( i ) < value.val ) {
value.val = values( i );
value.loc = i;
}
}
};
struct MaxLocFunctor {
Kokkos::View< const Scalar*, ExecSpace > values;
KOKKOS_INLINE_FUNCTION
void operator()( const int & i, typename Kokkos::Experimental::MaxLoc< Scalar, int >::value_type & value ) const {
if ( values( i ) > value.val ) {
value.val = values( i );
value.loc = i;
}
}
};
struct MinMaxLocFunctor {
Kokkos::View< const Scalar*, ExecSpace > values;
KOKKOS_INLINE_FUNCTION
void operator()( const int & i, typename Kokkos::Experimental::MinMaxLoc< Scalar, int >::value_type & value ) const {
if ( values( i ) > value.max_val ) {
value.max_val = values( i );
value.max_loc = i;
}
if ( values( i ) < value.min_val ) {
value.min_val = values( i );
value.min_loc = i;
}
}
};
struct BAndFunctor {
Kokkos::View< const Scalar*, ExecSpace > values;
KOKKOS_INLINE_FUNCTION
void operator()( const int & i, Scalar & value ) const {
value = value & values( i );
}
};
struct BOrFunctor {
Kokkos::View< const Scalar*, ExecSpace > values;
KOKKOS_INLINE_FUNCTION
void operator()( const int & i, Scalar & value ) const {
value = value | values( i );
}
};
struct BXorFunctor {
Kokkos::View< const Scalar*, ExecSpace > values;
KOKKOS_INLINE_FUNCTION
void operator()( const int & i, Scalar & value ) const {
value = value ^ values( i );
}
};
struct LAndFunctor {
Kokkos::View< const Scalar*, ExecSpace > values;
KOKKOS_INLINE_FUNCTION
void operator()( const int & i, Scalar & value ) const {
value = value && values( i );
}
};
struct LOrFunctor {
Kokkos::View< const Scalar*, ExecSpace > values;
KOKKOS_INLINE_FUNCTION
void operator()( const int & i, Scalar & value ) const {
value = value || values( i );
}
};
struct LXorFunctor {
Kokkos::View< const Scalar*, ExecSpace > values;
KOKKOS_INLINE_FUNCTION
void operator()( const int & i, Scalar & value ) const {
value = value ? ( !values( i ) ) : values( i );
}
};
static void test_sum( int N ) {
Kokkos::View< Scalar*, ExecSpace > values( "Values", N );
auto h_values = Kokkos::create_mirror_view( values );
Scalar reference_sum = 0;
for ( int i = 0; i < N; i++ ) {
h_values( i ) = (Scalar) ( rand() % 100 );
reference_sum += h_values( i );
}
Kokkos::deep_copy( values, h_values );
SumFunctor f;
f.values = values;
Scalar init = 0;
{
Scalar sum_scalar = init;
Kokkos::Experimental::Sum< Scalar > reducer_scalar( sum_scalar );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_scalar );
ASSERT_EQ( sum_scalar, reference_sum );
Scalar sum_scalar_view = reducer_scalar.result_view()();
ASSERT_EQ( sum_scalar_view, reference_sum );
}
{
Scalar sum_scalar_init = init;
Kokkos::Experimental::Sum< Scalar > reducer_scalar_init( sum_scalar_init, init );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_scalar_init );
ASSERT_EQ( sum_scalar_init, reference_sum );
Scalar sum_scalar_init_view = reducer_scalar_init.result_view()();
ASSERT_EQ( sum_scalar_init_view, reference_sum );
}
{
Kokkos::View< Scalar, Kokkos::HostSpace> sum_view( "View" );
sum_view() = init;
Kokkos::Experimental::Sum< Scalar > reducer_view( sum_view );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_view );
Scalar sum_view_scalar = sum_view();
ASSERT_EQ( sum_view_scalar, reference_sum );
Scalar sum_view_view = reducer_view.result_view()();
ASSERT_EQ( sum_view_view, reference_sum );
}
{
Kokkos::View< Scalar, Kokkos::HostSpace > sum_view_init( "View" );
sum_view_init() = init;
Kokkos::Experimental::Sum< Scalar > reducer_view_init( sum_view_init, init );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_view_init );
Scalar sum_view_init_scalar = sum_view_init();
ASSERT_EQ( sum_view_init_scalar, reference_sum );
Scalar sum_view_init_view = reducer_view_init.result_view()();
ASSERT_EQ( sum_view_init_view, reference_sum );
}
}
static void test_prod( int N ) {
Kokkos::View< Scalar*, ExecSpace > values( "Values", N );
auto h_values = Kokkos::create_mirror_view( values );
Scalar reference_prod = 1;
for ( int i = 0; i < N; i++ ) {
h_values( i ) = (Scalar) ( rand() % 4 + 1 );
reference_prod *= h_values( i );
}
Kokkos::deep_copy( values, h_values );
ProdFunctor f;
f.values = values;
Scalar init = 1;
if ( std::is_arithmetic< Scalar >::value )
{
Scalar prod_scalar = init;
Kokkos::Experimental::Prod< Scalar > reducer_scalar( prod_scalar );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_scalar );
ASSERT_EQ( prod_scalar, reference_prod );
Scalar prod_scalar_view = reducer_scalar.result_view()();
ASSERT_EQ( prod_scalar_view, reference_prod );
}
{
Scalar prod_scalar_init = init;
Kokkos::Experimental::Prod< Scalar > reducer_scalar_init( prod_scalar_init, init );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_scalar_init );
ASSERT_EQ( prod_scalar_init, reference_prod );
Scalar prod_scalar_init_view = reducer_scalar_init.result_view()();
ASSERT_EQ( prod_scalar_init_view, reference_prod );
}
if ( std::is_arithmetic< Scalar >::value )
{
Kokkos::View< Scalar, Kokkos::HostSpace > prod_view( "View" );
prod_view() = init;
Kokkos::Experimental::Prod< Scalar > reducer_view( prod_view );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_view );
Scalar prod_view_scalar = prod_view();
ASSERT_EQ( prod_view_scalar, reference_prod );
Scalar prod_view_view = reducer_view.result_view()();
ASSERT_EQ( prod_view_view, reference_prod );
}
{
Kokkos::View< Scalar, Kokkos::HostSpace > prod_view_init( "View" );
prod_view_init() = init;
Kokkos::Experimental::Prod< Scalar > reducer_view_init( prod_view_init, init );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_view_init );
Scalar prod_view_init_scalar = prod_view_init();
ASSERT_EQ( prod_view_init_scalar, reference_prod );
Scalar prod_view_init_view = reducer_view_init.result_view()();
ASSERT_EQ( prod_view_init_view, reference_prod );
}
}
static void test_min( int N ) {
Kokkos::View< Scalar*, ExecSpace > values( "Values", N );
auto h_values = Kokkos::create_mirror_view( values );
Scalar reference_min = std::numeric_limits< Scalar >::max();
for ( int i = 0; i < N; i++ ) {
h_values( i ) = (Scalar) ( rand() % 100000 );
if ( h_values( i ) < reference_min ) reference_min = h_values( i );
}
Kokkos::deep_copy( values, h_values );
MinFunctor f;
f.values = values;
Scalar init = std::numeric_limits< Scalar >::max();
{
Scalar min_scalar = init;
Kokkos::Experimental::Min< Scalar > reducer_scalar( min_scalar );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_scalar );
ASSERT_EQ( min_scalar, reference_min );
Scalar min_scalar_view = reducer_scalar.result_view()();
ASSERT_EQ( min_scalar_view, reference_min );
}
{
Scalar min_scalar_init = init;
Kokkos::Experimental::Min< Scalar > reducer_scalar_init( min_scalar_init, init );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_scalar_init );
ASSERT_EQ( min_scalar_init, reference_min );
Scalar min_scalar_init_view = reducer_scalar_init.result_view()();
ASSERT_EQ( min_scalar_init_view, reference_min );
}
{
Kokkos::View< Scalar, Kokkos::HostSpace > min_view( "View" );
min_view() = init;
Kokkos::Experimental::Min< Scalar > reducer_view( min_view );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_view );
Scalar min_view_scalar = min_view();
ASSERT_EQ( min_view_scalar, reference_min );
Scalar min_view_view = reducer_view.result_view()();
ASSERT_EQ( min_view_view, reference_min );
}
{
Kokkos::View< Scalar, Kokkos::HostSpace > min_view_init( "View" );
min_view_init() = init;
Kokkos::Experimental::Min< Scalar > reducer_view_init( min_view_init, init );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_view_init );
Scalar min_view_init_scalar = min_view_init();
ASSERT_EQ( min_view_init_scalar, reference_min );
Scalar min_view_init_view = reducer_view_init.result_view()();
ASSERT_EQ( min_view_init_view, reference_min );
}
}
static void test_max( int N ) {
Kokkos::View< Scalar*, ExecSpace > values( "Values", N );
auto h_values = Kokkos::create_mirror_view( values );
Scalar reference_max = std::numeric_limits< Scalar >::min();
for ( int i = 0; i < N; i++ ) {
h_values( i ) = (Scalar) ( rand() % 100000 + 1 );
if ( h_values( i ) > reference_max ) reference_max = h_values( i );
}
Kokkos::deep_copy( values, h_values );
MaxFunctor f;
f.values = values;
Scalar init = std::numeric_limits< Scalar >::min();
{
Scalar max_scalar = init;
Kokkos::Experimental::Max< Scalar > reducer_scalar( max_scalar );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_scalar );
ASSERT_EQ( max_scalar, reference_max );
Scalar max_scalar_view = reducer_scalar.result_view()();
ASSERT_EQ( max_scalar_view, reference_max );
}
{
Scalar max_scalar_init = init;
Kokkos::Experimental::Max< Scalar > reducer_scalar_init( max_scalar_init, init );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_scalar_init );
ASSERT_EQ( max_scalar_init, reference_max );
Scalar max_scalar_init_view = reducer_scalar_init.result_view()();
ASSERT_EQ( max_scalar_init_view, reference_max );
}
{
Kokkos::View< Scalar, Kokkos::HostSpace > max_view( "View" );
max_view() = init;
Kokkos::Experimental::Max< Scalar > reducer_view( max_view );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_view );
Scalar max_view_scalar = max_view();
ASSERT_EQ( max_view_scalar, reference_max );
Scalar max_view_view = reducer_view.result_view()();
ASSERT_EQ( max_view_view, reference_max );
}
{
Kokkos::View< Scalar, Kokkos::HostSpace > max_view_init( "View" );
max_view_init() = init;
Kokkos::Experimental::Max< Scalar > reducer_view_init( max_view_init, init );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_view_init );
Scalar max_view_init_scalar = max_view_init();
ASSERT_EQ( max_view_init_scalar, reference_max );
Scalar max_view_init_view = reducer_view_init.result_view()();
ASSERT_EQ( max_view_init_view, reference_max );
}
}
static void test_minloc( int N ) {
typedef typename Kokkos::Experimental::MinLoc< Scalar, int >::value_type value_type;
Kokkos::View< Scalar*, ExecSpace > values( "Values", N );
auto h_values = Kokkos::create_mirror_view( values );
Scalar reference_min = std::numeric_limits< Scalar >::max();
int reference_loc = -1;
for ( int i = 0; i < N; i++ ) {
h_values( i ) = (Scalar) ( rand() % 100000 );
if ( h_values( i ) < reference_min ) {
reference_min = h_values( i );
reference_loc = i;
}
else if ( h_values( i ) == reference_min ) {
// Make min unique.
h_values( i ) += std::numeric_limits< Scalar >::epsilon();
}
}
Kokkos::deep_copy( values, h_values );
MinLocFunctor f;
f.values = values;
Scalar init = std::numeric_limits< Scalar >::max();
{
value_type min_scalar;
Kokkos::Experimental::MinLoc< Scalar, int > reducer_scalar( min_scalar );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_scalar );
ASSERT_EQ( min_scalar.val, reference_min );
ASSERT_EQ( min_scalar.loc, reference_loc );
value_type min_scalar_view = reducer_scalar.result_view()();
ASSERT_EQ( min_scalar_view.val, reference_min );
ASSERT_EQ( min_scalar_view.loc, reference_loc );
}
{
value_type min_scalar_init;
Kokkos::Experimental::MinLoc< Scalar, int > reducer_scalar_init( min_scalar_init, init );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_scalar_init );
ASSERT_EQ( min_scalar_init.val, reference_min );
ASSERT_EQ( min_scalar_init.loc, reference_loc );
value_type min_scalar_init_view = reducer_scalar_init.result_view()();
ASSERT_EQ( min_scalar_init_view.val, reference_min );
ASSERT_EQ( min_scalar_init_view.loc, reference_loc );
}
{
Kokkos::View< value_type, Kokkos::HostSpace > min_view( "View" );
Kokkos::Experimental::MinLoc< Scalar, int > reducer_view( min_view );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_view );
value_type min_view_scalar = min_view();
ASSERT_EQ( min_view_scalar.val, reference_min );
ASSERT_EQ( min_view_scalar.loc, reference_loc );
value_type min_view_view = reducer_view.result_view()();
ASSERT_EQ( min_view_view.val, reference_min );
ASSERT_EQ( min_view_view.loc, reference_loc );
}
{
Kokkos::View< value_type, Kokkos::HostSpace > min_view_init( "View" );
Kokkos::Experimental::MinLoc< Scalar, int > reducer_view_init( min_view_init, init );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_view_init );
value_type min_view_init_scalar = min_view_init();
ASSERT_EQ( min_view_init_scalar.val, reference_min );
ASSERT_EQ( min_view_init_scalar.loc, reference_loc );
value_type min_view_init_view = reducer_view_init.result_view()();
ASSERT_EQ( min_view_init_view.val, reference_min );
ASSERT_EQ( min_view_init_view.loc, reference_loc );
}
}
static void test_maxloc( int N ) {
typedef typename Kokkos::Experimental::MaxLoc< Scalar, int >::value_type value_type;
Kokkos::View< Scalar*, ExecSpace > values( "Values", N );
auto h_values = Kokkos::create_mirror_view( values );
Scalar reference_max = std::numeric_limits< Scalar >::min();
int reference_loc = -1;
for ( int i = 0; i < N; i++ ) {
h_values( i ) = (Scalar) ( rand() % 100000 );
if ( h_values( i ) > reference_max ) {
reference_max = h_values( i );
reference_loc = i;
}
else if ( h_values( i ) == reference_max ) {
// Make max unique.
h_values( i ) -= std::numeric_limits< Scalar >::epsilon();
}
}
Kokkos::deep_copy( values, h_values );
MaxLocFunctor f;
f.values = values;
Scalar init = std::numeric_limits< Scalar >::min();
{
value_type max_scalar;
Kokkos::Experimental::MaxLoc< Scalar, int > reducer_scalar( max_scalar );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_scalar );
ASSERT_EQ( max_scalar.val, reference_max );
ASSERT_EQ( max_scalar.loc, reference_loc );
value_type max_scalar_view = reducer_scalar.result_view()();
ASSERT_EQ( max_scalar_view.val, reference_max );
ASSERT_EQ( max_scalar_view.loc, reference_loc );
}
{
value_type max_scalar_init;
Kokkos::Experimental::MaxLoc< Scalar, int > reducer_scalar_init( max_scalar_init, init );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_scalar_init );
ASSERT_EQ( max_scalar_init.val, reference_max );
ASSERT_EQ( max_scalar_init.loc, reference_loc );
value_type max_scalar_init_view = reducer_scalar_init.result_view()();
ASSERT_EQ( max_scalar_init_view.val, reference_max );
ASSERT_EQ( max_scalar_init_view.loc, reference_loc );
}
{
Kokkos::View< value_type, Kokkos::HostSpace > max_view( "View" );
Kokkos::Experimental::MaxLoc< Scalar, int > reducer_view( max_view );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_view );
value_type max_view_scalar = max_view();
ASSERT_EQ( max_view_scalar.val, reference_max );
ASSERT_EQ( max_view_scalar.loc, reference_loc );
value_type max_view_view = reducer_view.result_view()();
ASSERT_EQ( max_view_view.val, reference_max );
ASSERT_EQ( max_view_view.loc, reference_loc );
}
{
Kokkos::View< value_type, Kokkos::HostSpace > max_view_init( "View" );
Kokkos::Experimental::MaxLoc< Scalar, int > reducer_view_init( max_view_init, init );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_view_init );
value_type max_view_init_scalar = max_view_init();
ASSERT_EQ( max_view_init_scalar.val, reference_max );
ASSERT_EQ( max_view_init_scalar.loc, reference_loc );
value_type max_view_init_view = reducer_view_init.result_view()();
ASSERT_EQ( max_view_init_view.val, reference_max );
ASSERT_EQ( max_view_init_view.loc, reference_loc );
}
}
static void test_minmaxloc( int N ) {
typedef typename Kokkos::Experimental::MinMaxLoc< Scalar, int >::value_type value_type;
Kokkos::View< Scalar*, ExecSpace > values( "Values", N );
auto h_values = Kokkos::create_mirror_view( values );
Scalar reference_max = std::numeric_limits< Scalar >::min();
Scalar reference_min = std::numeric_limits< Scalar >::max();
int reference_minloc = -1;
int reference_maxloc = -1;
for ( int i = 0; i < N; i++ ) {
h_values( i ) = (Scalar) ( rand() % 100000 );
}
for ( int i = 0; i < N; i++ ) {
if ( h_values( i ) > reference_max ) {
reference_max = h_values( i );
reference_maxloc = i;
}
else if ( h_values( i ) == reference_max ) {
// Make max unique.
h_values( i ) -= std::numeric_limits< Scalar >::epsilon();
}
}
for ( int i = 0; i < N; i++ ) {
if ( h_values( i ) < reference_min ) {
reference_min = h_values( i );
reference_minloc = i;
}
else if ( h_values( i ) == reference_min ) {
// Make min unique.
h_values( i ) += std::numeric_limits< Scalar >::epsilon();
}
}
Kokkos::deep_copy( values, h_values );
MinMaxLocFunctor f;
f.values = values;
Scalar init_min = std::numeric_limits< Scalar >::max();
Scalar init_max = std::numeric_limits< Scalar >::min();
{
value_type minmax_scalar;
Kokkos::Experimental::MinMaxLoc< Scalar, int > reducer_scalar( minmax_scalar );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_scalar );
ASSERT_EQ( minmax_scalar.min_val, reference_min );
for ( int i = 0; i < N; i++ ) {
if ( ( i == minmax_scalar.min_loc ) && ( h_values( i ) == reference_min ) ) {
reference_minloc = i;
}
}
ASSERT_EQ( minmax_scalar.min_loc, reference_minloc );
ASSERT_EQ( minmax_scalar.max_val, reference_max );
for ( int i = 0; i < N; i++ ) {
if ( ( i == minmax_scalar.max_loc ) && ( h_values( i ) == reference_max ) ) {
reference_maxloc = i;
}
}
ASSERT_EQ( minmax_scalar.max_loc, reference_maxloc );
value_type minmax_scalar_view = reducer_scalar.result_view()();
ASSERT_EQ( minmax_scalar_view.min_val, reference_min );
ASSERT_EQ( minmax_scalar_view.min_loc, reference_minloc );
ASSERT_EQ( minmax_scalar_view.max_val, reference_max );
ASSERT_EQ( minmax_scalar_view.max_loc, reference_maxloc );
}
{
value_type minmax_scalar_init;
Kokkos::Experimental::MinMaxLoc< Scalar, int > reducer_scalar_init( minmax_scalar_init, init_min, init_max );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_scalar_init );
ASSERT_EQ( minmax_scalar_init.min_val, reference_min );
ASSERT_EQ( minmax_scalar_init.min_loc, reference_minloc );
ASSERT_EQ( minmax_scalar_init.max_val, reference_max );
ASSERT_EQ( minmax_scalar_init.max_loc, reference_maxloc );
value_type minmax_scalar_init_view = reducer_scalar_init.result_view()();
ASSERT_EQ( minmax_scalar_init_view.min_val, reference_min );
ASSERT_EQ( minmax_scalar_init_view.min_loc, reference_minloc );
ASSERT_EQ( minmax_scalar_init_view.max_val, reference_max );
ASSERT_EQ( minmax_scalar_init_view.max_loc, reference_maxloc );
}
{
Kokkos::View< value_type, Kokkos::HostSpace > minmax_view( "View" );
Kokkos::Experimental::MinMaxLoc< Scalar, int > reducer_view( minmax_view );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_view );
value_type minmax_view_scalar = minmax_view();
ASSERT_EQ( minmax_view_scalar.min_val, reference_min );
ASSERT_EQ( minmax_view_scalar.min_loc, reference_minloc );
ASSERT_EQ( minmax_view_scalar.max_val, reference_max );
ASSERT_EQ( minmax_view_scalar.max_loc, reference_maxloc );
value_type minmax_view_view = reducer_view.result_view()();
ASSERT_EQ( minmax_view_view.min_val, reference_min );
ASSERT_EQ( minmax_view_view.min_loc, reference_minloc );
ASSERT_EQ( minmax_view_view.max_val, reference_max );
ASSERT_EQ( minmax_view_view.max_loc, reference_maxloc );
}
{
Kokkos::View< value_type, Kokkos::HostSpace > minmax_view_init( "View" );
Kokkos::Experimental::MinMaxLoc< Scalar, int > reducer_view_init( minmax_view_init, init_min, init_max );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_view_init );
value_type minmax_view_init_scalar = minmax_view_init();
ASSERT_EQ( minmax_view_init_scalar.min_val, reference_min );
ASSERT_EQ( minmax_view_init_scalar.min_loc, reference_minloc );
ASSERT_EQ( minmax_view_init_scalar.max_val, reference_max );
ASSERT_EQ( minmax_view_init_scalar.max_loc, reference_maxloc );
value_type minmax_view_init_view = reducer_view_init.result_view()();
ASSERT_EQ( minmax_view_init_view.min_val, reference_min );
ASSERT_EQ( minmax_view_init_view.min_loc, reference_minloc );
ASSERT_EQ( minmax_view_init_view.max_val, reference_max );
ASSERT_EQ( minmax_view_init_view.max_loc, reference_maxloc );
}
}
static void test_BAnd( int N ) {
Kokkos::View< Scalar*, ExecSpace > values( "Values", N );
auto h_values = Kokkos::create_mirror_view( values );
Scalar reference_band = Scalar() | ( ~Scalar() );
for ( int i = 0; i < N; i++ ) {
h_values( i ) = (Scalar) ( rand() % 100000 + 1 );
reference_band = reference_band & h_values( i );
}
Kokkos::deep_copy( values, h_values );
BAndFunctor f;
f.values = values;
Scalar init = Scalar() | ( ~Scalar() );
{
Scalar band_scalar = init;
Kokkos::Experimental::BAnd< Scalar > reducer_scalar( band_scalar );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_scalar );
ASSERT_EQ( band_scalar, reference_band );
Scalar band_scalar_view = reducer_scalar.result_view()();
ASSERT_EQ( band_scalar_view, reference_band );
}
{
Kokkos::View< Scalar, Kokkos::HostSpace > band_view( "View" );
band_view() = init;
Kokkos::Experimental::BAnd< Scalar > reducer_view( band_view );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_view );
Scalar band_view_scalar = band_view();
ASSERT_EQ( band_view_scalar, reference_band );
Scalar band_view_view = reducer_view.result_view()();
ASSERT_EQ( band_view_view, reference_band );
}
}
static void test_BOr( int N ) {
Kokkos::View< Scalar*, ExecSpace > values( "Values", N );
auto h_values = Kokkos::create_mirror_view( values );
Scalar reference_bor = Scalar() & ( ~Scalar() );
for ( int i = 0; i < N; i++ ) {
h_values( i ) = (Scalar) ( ( rand() % 100000 + 1 ) * 2 );
reference_bor = reference_bor | h_values( i );
}
Kokkos::deep_copy( values, h_values );
BOrFunctor f;
f.values = values;
Scalar init = Scalar() & ( ~Scalar() );
{
Scalar bor_scalar = init;
Kokkos::Experimental::BOr< Scalar > reducer_scalar( bor_scalar );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_scalar );
ASSERT_EQ( bor_scalar, reference_bor );
Scalar bor_scalar_view = reducer_scalar.result_view()();
ASSERT_EQ( bor_scalar_view, reference_bor );
}
{
Kokkos::View< Scalar, Kokkos::HostSpace > bor_view( "View" );
bor_view() = init;
Kokkos::Experimental::BOr< Scalar > reducer_view( bor_view );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_view );
Scalar bor_view_scalar = bor_view();
ASSERT_EQ( bor_view_scalar, reference_bor );
Scalar bor_view_view = reducer_view.result_view()();
ASSERT_EQ( bor_view_view, reference_bor );
}
}
static void test_BXor( int N ) {
Kokkos::View< Scalar*, ExecSpace > values( "Values", N );
auto h_values = Kokkos::create_mirror_view( values );
Scalar reference_bxor = Scalar() & ( ~Scalar() );
for ( int i = 0; i < N; i++ ) {
h_values( i ) = (Scalar) ( ( rand() % 100000 + 1 ) * 2 );
reference_bxor = reference_bxor ^ h_values( i );
}
Kokkos::deep_copy( values, h_values );
BXorFunctor f;
f.values = values;
Scalar init = Scalar() & ( ~Scalar() );
{
Scalar bxor_scalar = init;
Kokkos::Experimental::BXor< Scalar > reducer_scalar( bxor_scalar );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_scalar );
ASSERT_EQ( bxor_scalar, reference_bxor );
Scalar bxor_scalar_view = reducer_scalar.result_view()();
ASSERT_EQ( bxor_scalar_view, reference_bxor );
}
{
Kokkos::View< Scalar, Kokkos::HostSpace > bxor_view( "View" );
bxor_view() = init;
Kokkos::Experimental::BXor< Scalar > reducer_view( bxor_view );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_view );
Scalar bxor_view_scalar = bxor_view();
ASSERT_EQ( bxor_view_scalar, reference_bxor );
Scalar bxor_view_view = reducer_view.result_view()();
ASSERT_EQ( bxor_view_view, reference_bxor );
}
}
static void test_LAnd( int N ) {
Kokkos::View< Scalar*, ExecSpace > values( "Values", N );
auto h_values = Kokkos::create_mirror_view( values );
Scalar reference_land = 1;
for ( int i = 0; i < N; i++ ) {
h_values( i ) = (Scalar) ( rand() % 2 );
reference_land = reference_land && h_values( i );
}
Kokkos::deep_copy( values, h_values );
LAndFunctor f;
f.values = values;
Scalar init = 1;
{
Scalar land_scalar = init;
Kokkos::Experimental::LAnd< Scalar > reducer_scalar( land_scalar );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_scalar );
ASSERT_EQ( land_scalar, reference_land );
Scalar land_scalar_view = reducer_scalar.result_view()();
ASSERT_EQ( land_scalar_view, reference_land );
}
{
Kokkos::View< Scalar, Kokkos::HostSpace > land_view( "View" );
land_view() = init;
Kokkos::Experimental::LAnd< Scalar > reducer_view( land_view );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_view );
Scalar land_view_scalar = land_view();
ASSERT_EQ( land_view_scalar, reference_land );
Scalar land_view_view = reducer_view.result_view()();
ASSERT_EQ( land_view_view, reference_land );
}
}
static void test_LOr( int N ) {
Kokkos::View< Scalar*, ExecSpace > values( "Values", N );
auto h_values = Kokkos::create_mirror_view( values );
Scalar reference_lor = 0;
for ( int i = 0; i < N; i++ ) {
h_values( i ) = (Scalar) ( rand() % 2 );
reference_lor = reference_lor || h_values( i );
}
Kokkos::deep_copy( values, h_values );
LOrFunctor f;
f.values = values;
Scalar init = 0;
{
Scalar lor_scalar = init;
Kokkos::Experimental::LOr< Scalar > reducer_scalar( lor_scalar );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_scalar );
ASSERT_EQ( lor_scalar, reference_lor );
Scalar lor_scalar_view = reducer_scalar.result_view()();
ASSERT_EQ( lor_scalar_view, reference_lor );
}
{
Kokkos::View< Scalar, Kokkos::HostSpace > lor_view( "View" );
lor_view() = init;
Kokkos::Experimental::LOr< Scalar > reducer_view( lor_view );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_view );
Scalar lor_view_scalar = lor_view();
ASSERT_EQ( lor_view_scalar, reference_lor );
Scalar lor_view_view = reducer_view.result_view()();
ASSERT_EQ( lor_view_view, reference_lor );
}
}
static void test_LXor( int N ) {
Kokkos::View< Scalar*, ExecSpace > values( "Values", N );
auto h_values = Kokkos::create_mirror_view( values );
Scalar reference_lxor = 0;
for ( int i = 0; i < N; i++ ) {
h_values( i ) = (Scalar) ( rand() % 2 );
reference_lxor = reference_lxor ? ( !h_values( i ) ) : h_values( i );
}
Kokkos::deep_copy( values, h_values );
LXorFunctor f;
f.values = values;
Scalar init = 0;
{
Scalar lxor_scalar = init;
Kokkos::Experimental::LXor< Scalar > reducer_scalar( lxor_scalar );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_scalar );
ASSERT_EQ( lxor_scalar, reference_lxor );
Scalar lxor_scalar_view = reducer_scalar.result_view()();
ASSERT_EQ( lxor_scalar_view, reference_lxor );
}
{
Kokkos::View< Scalar, Kokkos::HostSpace > lxor_view( "View" );
lxor_view() = init;
Kokkos::Experimental::LXor< Scalar > reducer_view( lxor_view );
Kokkos::parallel_reduce( Kokkos::RangePolicy< ExecSpace >( 0, N ), f, reducer_view );
Scalar lxor_view_scalar = lxor_view();
ASSERT_EQ( lxor_view_scalar, reference_lxor );
Scalar lxor_view_view = reducer_view.result_view()();
ASSERT_EQ( lxor_view_view, reference_lxor );
}
}
static void execute_float() {
test_sum( 10001 );
test_prod( 35 );
test_min( 10003 );
test_minloc( 10003 );
test_max( 10007 );
test_maxloc( 10007 );
test_minmaxloc( 10007 );
}
static void execute_integer() {
test_sum( 10001 );
test_prod( 35 );
test_min( 10003 );
test_minloc( 10003 );
test_max( 10007 );
test_maxloc( 10007 );
test_minmaxloc( 10007 );
test_BAnd( 35 );
test_BOr( 35 );
test_BXor( 35 );
test_LAnd( 35 );
test_LOr( 35 );
test_LXor( 35 );
}
static void execute_basic() {
test_sum( 10001 );
test_prod( 35 );
}
};
} // namespace Test