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Kokkos_OpenMPTarget_Exec.hpp
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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
*/
#ifndef KOKKOS_OPENMPTARGETEXEC_HPP
#define KOKKOS_OPENMPTARGETEXEC_HPP
#include <impl/Kokkos_Traits.hpp>
#include <impl/Kokkos_Spinwait.hpp>
#include <Kokkos_Atomic.hpp>
#include <iostream>
#include <sstream>
#include <fstream>
namespace Kokkos {
namespace Impl {
//----------------------------------------------------------------------------
/** \brief Data for OpenMPTarget thread execution */
class OpenMPTargetExec {
public:
enum { MAX_ACTIVE_THREADS = 256*8*56*4 };
enum { MAX_ACTIVE_TEAMS = MAX_ACTIVE_THREADS/32 };
private:
static void* scratch_ptr;
public:
static void verify_is_process( const char * const );
static void verify_initialized( const char * const );
static void* get_scratch_ptr();
static void clear_scratch();
static void resize_scratch( int64_t reduce_bytes , int64_t team_reduce_bytes, int64_t team_shared_bytes, int64_t thread_local_bytes );
static void* m_scratch_ptr;
static int64_t m_scratch_size;
};
} // namespace Impl
} // namespace Kokkos
//----------------------------------------------------------------------------
//----------------------------------------------------------------------------
namespace Kokkos {
namespace Impl {
class OpenMPTargetExecTeamMember {
public:
enum { TEAM_REDUCE_SIZE = 512 };
/** \brief Thread states for team synchronization */
enum { Active = 0 , Rendezvous = 1 };
typedef Kokkos::Experimental::OpenMPTarget execution_space ;
typedef execution_space::scratch_memory_space scratch_memory_space ;
scratch_memory_space m_team_shared ;
int m_team_scratch_size[2] ;
int m_team_rank ;
int m_team_size ;
int m_league_rank ;
int m_league_size ;
int m_vector_length ;
int m_vector_lane ;
void* m_glb_scratch ;
/*
// Fan-in team threads, root of the fan-in which does not block returns true
inline
bool team_fan_in() const
{
memory_fence();
for ( int n = 1 , j ; ( ( j = m_team_rank_rev + n ) < m_team_size ) && ! ( m_team_rank_rev & n ) ; n <<= 1 ) {
m_exec.pool_rev( m_team_base_rev + j )->state_wait( Active );
}
if ( m_team_rank_rev ) {
m_exec.state_set( Rendezvous );
memory_fence();
m_exec.state_wait( Rendezvous );
}
return 0 == m_team_rank_rev ;
}
inline
void team_fan_out() const
{
memory_fence();
for ( int n = 1 , j ; ( ( j = m_team_rank_rev + n ) < m_team_size ) && ! ( m_team_rank_rev & n ) ; n <<= 1 ) {
m_exec.pool_rev( m_team_base_rev + j )->state_set( Active );
memory_fence();
}
}
*/
public:
KOKKOS_INLINE_FUNCTION
const execution_space::scratch_memory_space& team_shmem() const
{ return m_team_shared.set_team_thread_mode(0,1,0) ; }
KOKKOS_INLINE_FUNCTION
const execution_space::scratch_memory_space& team_scratch(int) const
{ return m_team_shared.set_team_thread_mode(0,1,0) ; }
KOKKOS_INLINE_FUNCTION
const execution_space::scratch_memory_space& thread_scratch(int) const
{ return m_team_shared.set_team_thread_mode(0,team_size(),team_rank()) ; }
KOKKOS_INLINE_FUNCTION int league_rank() const { return m_league_rank ; }
KOKKOS_INLINE_FUNCTION int league_size() const { return m_league_size ; }
KOKKOS_INLINE_FUNCTION int team_rank() const { return m_team_rank ; }
KOKKOS_INLINE_FUNCTION int team_size() const { return m_team_size ; }
KOKKOS_INLINE_FUNCTION void team_barrier() const
{
#pragma omp barrier
}
template<class ValueType>
KOKKOS_INLINE_FUNCTION
void team_broadcast(ValueType& value, const int& thread_id) const
{
/*#if ! defined( KOKKOS_ACTIVE_EXECUTION_MEMORY_SPACE_HOST )
{ }
#else
// Make sure there is enough scratch space:
typedef typename if_c< sizeof(ValueType) < TEAM_REDUCE_SIZE
, ValueType , void >::type type ;
type * const local_value = ((type*) m_exec.scratch_thread());
if(team_rank() == thread_id)
*local_value = value;
memory_fence();
team_barrier();
value = *local_value;
#endif*/
}
template< class ValueType, class JoinOp >
KOKKOS_INLINE_FUNCTION ValueType
team_reduce( const ValueType & value
, const JoinOp & op_in ) const {
#pragma omp barrier
typedef ValueType value_type;
const JoinLambdaAdapter<value_type,JoinOp> op(op_in);
// Make sure there is enough scratch space:
typedef typename if_c< sizeof(value_type) < TEAM_REDUCE_SIZE
, value_type , void >::type type ;
const int n_values = TEAM_REDUCE_SIZE/sizeof(value_type);
type * team_scratch = (type*) ((char*)m_glb_scratch + TEAM_REDUCE_SIZE*omp_get_team_num());
for(int i = m_team_rank; i < n_values; i+= m_team_size) {
team_scratch[i] = value_type();
}
#pragma omp barrier
for(int k=0; k<m_team_size; k+=n_values) {
if((k <= m_team_rank) && (k+n_values > m_team_rank))
team_scratch[m_team_rank%n_values]+=value;
#pragma omp barrier
}
for(int d = 1; d<n_values;d*=2) {
if((m_team_rank+d<n_values) && (m_team_rank%(2*d)==0)) {
team_scratch[m_team_rank] += team_scratch[m_team_rank+d];
}
#pragma omp barrier
}
return team_scratch[0];
}
/** \brief Intra-team exclusive prefix sum with team_rank() ordering
* with intra-team non-deterministic ordering accumulation.
*
* The global inter-team accumulation value will, at the end of the
* league's parallel execution, be the scan's total.
* Parallel execution ordering of the league's teams is non-deterministic.
* As such the base value for each team's scan operation is similarly
* non-deterministic.
*/
template< typename ArgType >
KOKKOS_INLINE_FUNCTION ArgType team_scan( const ArgType & value , ArgType * const global_accum ) const
{
/* // Make sure there is enough scratch space:
typedef typename if_c< sizeof(ArgType) < TEAM_REDUCE_SIZE , ArgType , void >::type type ;
volatile type * const work_value = ((type*) m_exec.scratch_thread());
*work_value = value ;
memory_fence();
if ( team_fan_in() ) {
// The last thread to synchronize returns true, all other threads wait for team_fan_out()
// m_team_base[0] == highest ranking team member
// m_team_base[ m_team_size - 1 ] == lowest ranking team member
//
// 1) copy from lower to higher rank, initialize lowest rank to zero
// 2) prefix sum from lowest to highest rank, skipping lowest rank
type accum = 0 ;
if ( global_accum ) {
for ( int i = m_team_size ; i-- ; ) {
type & val = *((type*) m_exec.pool_rev( m_team_base_rev + i )->scratch_thread());
accum += val ;
}
accum = atomic_fetch_add( global_accum , accum );
}
for ( int i = m_team_size ; i-- ; ) {
type & val = *((type*) m_exec.pool_rev( m_team_base_rev + i )->scratch_thread());
const type offset = accum ;
accum += val ;
val = offset ;
}
memory_fence();
}
team_fan_out();
return *work_value ;*/
return ArgType();
}
/** \brief Intra-team exclusive prefix sum with team_rank() ordering.
*
* The highest rank thread can compute the reduction total as
* reduction_total = dev.team_scan( value ) + value ;
*/
template< typename Type >
KOKKOS_INLINE_FUNCTION Type team_scan( const Type & value ) const
{ return this-> template team_scan<Type>( value , 0 ); }
//----------------------------------------
// Private for the driver
private:
typedef execution_space::scratch_memory_space space ;
public:
inline
OpenMPTargetExecTeamMember( const int league_rank, const int league_size, const int team_size, const int vector_length //const TeamPolicyInternal< OpenMPTarget, Properties ...> & team
, void* const glb_scratch
, const int shmem_size_L1
, const int shmem_size_L2
)
: m_team_shared(0,0)
, m_team_scratch_size{ shmem_size_L1 , shmem_size_L2 }
, m_team_rank(0)
, m_vector_length( vector_length )
, m_team_size( team_size )
, m_league_rank( league_rank )
, m_league_size( league_size )
, m_glb_scratch( glb_scratch )
{
const int omp_tid = omp_get_thread_num();
m_league_rank = league_rank;
m_team_rank = omp_tid/m_vector_length;
m_vector_lane = omp_tid%m_vector_length;
}
static inline int team_reduce_size() { return TEAM_REDUCE_SIZE ; }
};
template< class ... Properties >
class TeamPolicyInternal< Kokkos::Experimental::OpenMPTarget, Properties ... >: public PolicyTraits<Properties ...>
{
public:
//! Tag this class as a kokkos execution policy
typedef TeamPolicyInternal execution_policy ;
typedef PolicyTraits<Properties ... > traits;
TeamPolicyInternal& operator = (const TeamPolicyInternal& p) {
m_league_size = p.m_league_size;
m_team_size = p.m_team_size;
m_vector_length = p.m_vector_length;
m_team_alloc = p.m_team_alloc;
m_team_iter = p.m_team_iter;
m_team_scratch_size[0] = p.m_team_scratch_size[0];
m_thread_scratch_size[0] = p.m_thread_scratch_size[0];
m_team_scratch_size[1] = p.m_team_scratch_size[1];
m_thread_scratch_size[1] = p.m_thread_scratch_size[1];
m_chunk_size = p.m_chunk_size;
return *this;
}
//----------------------------------------
template< class FunctorType >
inline static
int team_size_max( const FunctorType & )
{ return 1024; }
template< class FunctorType >
inline static
int team_size_recommended( const FunctorType & )
{ return 256; }
template< class FunctorType >
inline static
int team_size_recommended( const FunctorType &, const int& vector_length)
{ return 256/vector_length; }
//----------------------------------------
private:
int m_league_size ;
int m_team_size ;
int m_vector_length;
int m_team_alloc ;
int m_team_iter ;
size_t m_team_scratch_size[2];
size_t m_thread_scratch_size[2];
int m_chunk_size;
inline void init( const int league_size_request
, const int team_size_request
, const int vector_length_request )
{
m_league_size = league_size_request ;
m_team_size = team_size_request;
m_vector_length = vector_length_request;
set_auto_chunk_size();
}
public:
inline int vector_length() const { return m_vector_length ; }
inline int team_size() const { return m_team_size ; }
inline int league_size() const { return m_league_size ; }
inline size_t scratch_size(const int& level, int team_size_ = -1) const {
if(team_size_ < 0)
team_size_ = m_team_size;
return m_team_scratch_size[level] + team_size_*m_thread_scratch_size[level] ;
}
/** \brief Specify league size, request team size */
TeamPolicyInternal( typename traits::execution_space &
, int league_size_request
, int team_size_request
, int vector_length_request = 1 )
: m_team_scratch_size { 0 , 0 }
, m_thread_scratch_size { 0 , 0 }
, m_chunk_size(0)
{ init( league_size_request , team_size_request , vector_length_request); }
TeamPolicyInternal( typename traits::execution_space &
, int league_size_request
, const Kokkos::AUTO_t & /* team_size_request */
, int vector_length_request = 1)
: m_team_scratch_size { 0 , 0 }
, m_thread_scratch_size { 0 , 0 }
, m_chunk_size(0)
{ init( league_size_request , 256/vector_length_request , vector_length_request ); }
TeamPolicyInternal( int league_size_request
, int team_size_request
, int vector_length_request = 1 )
: m_team_scratch_size { 0 , 0 }
, m_thread_scratch_size { 0 , 0 }
, m_chunk_size(0)
{ init( league_size_request , team_size_request , vector_length_request); }
TeamPolicyInternal( int league_size_request
, const Kokkos::AUTO_t & /* team_size_request */
, int vector_length_request = 1 )
: m_team_scratch_size { 0 , 0 }
, m_thread_scratch_size { 0 , 0 }
, m_chunk_size(0)
{ init( league_size_request , 256/vector_length_request , vector_length_request ); }
inline int team_alloc() const { return m_team_alloc ; }
inline int team_iter() const { return m_team_iter ; }
inline int chunk_size() const { return m_chunk_size ; }
/** \brief set chunk_size to a discrete value*/
inline TeamPolicyInternal set_chunk_size(typename traits::index_type chunk_size_) const {
TeamPolicyInternal p = *this;
p.m_chunk_size = chunk_size_;
return p;
}
inline TeamPolicyInternal set_scratch_size(const int& level, const PerTeamValue& per_team) const {
TeamPolicyInternal p = *this;
p.m_team_scratch_size[level] = per_team.value;
return p;
};
inline TeamPolicyInternal set_scratch_size(const int& level, const PerThreadValue& per_thread) const {
TeamPolicyInternal p = *this;
p.m_thread_scratch_size[level] = per_thread.value;
return p;
};
inline TeamPolicyInternal set_scratch_size(const int& level, const PerTeamValue& per_team, const PerThreadValue& per_thread) const {
TeamPolicyInternal p = *this;
p.m_team_scratch_size[level] = per_team.value;
p.m_thread_scratch_size[level] = per_thread.value;
return p;
};
private:
/** \brief finalize chunk_size if it was set to AUTO*/
inline void set_auto_chunk_size() {
int concurrency = traits::execution_space::thread_pool_size(0)/m_team_alloc;
if( concurrency==0 ) concurrency=1;
if(m_chunk_size > 0) {
if(!Impl::is_integral_power_of_two( m_chunk_size ))
Kokkos::abort("TeamPolicy blocking granularity must be power of two" );
}
int new_chunk_size = 1;
while(new_chunk_size*100*concurrency < m_league_size)
new_chunk_size *= 2;
if(new_chunk_size < 128) {
new_chunk_size = 1;
while( (new_chunk_size*40*concurrency < m_league_size ) && (new_chunk_size<128) )
new_chunk_size*=2;
}
m_chunk_size = new_chunk_size;
}
public:
typedef Impl::OpenMPTargetExecTeamMember member_type ;
};
} // namespace Impl
} // namespace Kokkos
//----------------------------------------------------------------------------
//----------------------------------------------------------------------------
namespace Kokkos {
namespace Experimental {
inline
int OpenMPTarget::thread_pool_size( int depth )
{
//return Impl::OpenMPTargetExec::pool_size(depth);
return omp_get_max_threads();
}
KOKKOS_INLINE_FUNCTION
int OpenMPTarget::thread_pool_rank()
{
return omp_get_thread_num();
}
} // namespace Experimental
} // namespace Kokkos
namespace Kokkos {
template<typename iType>
KOKKOS_INLINE_FUNCTION
Impl::TeamThreadRangeBoundariesStruct<iType,Impl::OpenMPTargetExecTeamMember>
TeamThreadRange(const Impl::OpenMPTargetExecTeamMember& thread, const iType& count) {
return Impl::TeamThreadRangeBoundariesStruct<iType,Impl::OpenMPTargetExecTeamMember>(thread,count);
}
template<typename iType>
KOKKOS_INLINE_FUNCTION
Impl::TeamThreadRangeBoundariesStruct<iType,Impl::OpenMPTargetExecTeamMember>
TeamThreadRange(const Impl::OpenMPTargetExecTeamMember& thread, const iType& begin, const iType& end) {
return Impl::TeamThreadRangeBoundariesStruct<iType,Impl::OpenMPTargetExecTeamMember>(thread,begin,end);
}
template<typename iType>
KOKKOS_INLINE_FUNCTION
Impl::ThreadVectorRangeBoundariesStruct<iType,Impl::OpenMPTargetExecTeamMember >
ThreadVectorRange(const Impl::OpenMPTargetExecTeamMember& thread, const iType& count) {
return Impl::ThreadVectorRangeBoundariesStruct<iType,Impl::OpenMPTargetExecTeamMember >(thread,count);
}
KOKKOS_INLINE_FUNCTION
Impl::ThreadSingleStruct<Impl::OpenMPTargetExecTeamMember> PerTeam(const Impl::OpenMPTargetExecTeamMember& thread) {
return Impl::ThreadSingleStruct<Impl::OpenMPTargetExecTeamMember>(thread);
}
KOKKOS_INLINE_FUNCTION
Impl::VectorSingleStruct<Impl::OpenMPTargetExecTeamMember> PerThread(const Impl::OpenMPTargetExecTeamMember& thread) {
return Impl::VectorSingleStruct<Impl::OpenMPTargetExecTeamMember>(thread);
}
} // namespace Kokkos
namespace Kokkos {
/** \brief Inter-thread parallel_for. Executes lambda(iType i) for each i=0..N-1.
*
* The range i=0..N-1 is mapped to all threads of the the calling thread team.
* This functionality requires C++11 support.*/
template<typename iType, class Lambda>
KOKKOS_INLINE_FUNCTION
void parallel_for(const Impl::TeamThreadRangeBoundariesStruct<iType,Impl::OpenMPTargetExecTeamMember>& loop_boundaries, const Lambda& lambda) {
for( iType i = loop_boundaries.start; i < loop_boundaries.end; i+=loop_boundaries.increment)
lambda(i);
}
/** \brief Inter-thread vector parallel_reduce. Executes lambda(iType i, ValueType & val) for each i=0..N-1.
*
* The range i=0..N-1 is mapped to all threads of the the calling thread team and a summation of
* val is performed and put into result. This functionality requires C++11 support.*/
template< typename iType, class Lambda, typename ValueType >
KOKKOS_INLINE_FUNCTION
void parallel_reduce(const Impl::TeamThreadRangeBoundariesStruct<iType,Impl::OpenMPTargetExecTeamMember>& loop_boundaries,
const Lambda & lambda, ValueType& result) {
result = ValueType();
for( iType i = loop_boundaries.start; i < loop_boundaries.end; i+=loop_boundaries.increment) {
ValueType tmp = ValueType();
lambda(i,tmp);
result+=tmp;
}
//result = loop_boundaries.thread.team_reduce(result,Impl::JoinAdd<ValueType>());
}
/** \brief Intra-thread vector parallel_reduce. Executes lambda(iType i, ValueType & val) for each i=0..N-1.
*
* The range i=0..N-1 is mapped to all vector lanes of the the calling thread and a reduction of
* val is performed using JoinType(ValueType& val, const ValueType& update) and put into init_result.
* The input value of init_result is used as initializer for temporary variables of ValueType. Therefore
* the input value should be the neutral element with respect to the join operation (e.g. '0 for +-' or
* '1 for *'). This functionality requires C++11 support.*/
template< typename iType, class Lambda, typename ValueType, class JoinType >
KOKKOS_INLINE_FUNCTION
void parallel_reduce(const Impl::TeamThreadRangeBoundariesStruct<iType,Impl::OpenMPTargetExecTeamMember>& loop_boundaries,
const Lambda & lambda, const JoinType& join, ValueType& init_result) {
ValueType result = init_result;
for( iType i = loop_boundaries.start; i < loop_boundaries.end; i+=loop_boundaries.increment) {
ValueType tmp = ValueType();
lambda(i,tmp);
join(result,tmp);
}
//init_result = loop_boundaries.thread.team_reduce(result,join);
}
} //namespace Kokkos
namespace Kokkos {
/** \brief Intra-thread vector parallel_for. Executes lambda(iType i) for each i=0..N-1.
*
* The range i=0..N-1 is mapped to all vector lanes of the the calling thread.
* This functionality requires C++11 support.*/
template<typename iType, class Lambda>
KOKKOS_INLINE_FUNCTION
void parallel_for(const Impl::ThreadVectorRangeBoundariesStruct<iType,Impl::OpenMPTargetExecTeamMember >&
loop_boundaries, const Lambda& lambda) {
for( iType i = loop_boundaries.start; i < loop_boundaries.end; i+=loop_boundaries.increment)
lambda(i);
}
/** \brief Intra-thread vector parallel_reduce. Executes lambda(iType i, ValueType & val) for each i=0..N-1.
*
* The range i=0..N-1 is mapped to all vector lanes of the the calling thread and a summation of
* val is performed and put into result. This functionality requires C++11 support.*/
template< typename iType, class Lambda, typename ValueType >
KOKKOS_INLINE_FUNCTION
void parallel_reduce(const Impl::ThreadVectorRangeBoundariesStruct<iType,Impl::OpenMPTargetExecTeamMember >&
loop_boundaries, const Lambda & lambda, ValueType& result) {
result = ValueType();
for( iType i = loop_boundaries.start; i < loop_boundaries.end; i+=loop_boundaries.increment) {
ValueType tmp = ValueType();
lambda(i,tmp);
result+=tmp;
}
}
/** \brief Intra-thread vector parallel_reduce. Executes lambda(iType i, ValueType & val) for each i=0..N-1.
*
* The range i=0..N-1 is mapped to all vector lanes of the the calling thread and a reduction of
* val is performed using JoinType(ValueType& val, const ValueType& update) and put into init_result.
* The input value of init_result is used as initializer for temporary variables of ValueType. Therefore
* the input value should be the neutral element with respect to the join operation (e.g. '0 for +-' or
* '1 for *'). This functionality requires C++11 support.*/
template< typename iType, class Lambda, typename ValueType, class JoinType >
KOKKOS_INLINE_FUNCTION
void parallel_reduce(const Impl::ThreadVectorRangeBoundariesStruct<iType,Impl::OpenMPTargetExecTeamMember >&
loop_boundaries, const Lambda & lambda, const JoinType& join, ValueType& init_result) {
ValueType result = init_result;
#ifdef KOKKOS_HAVE_PRAGMA_IVDEP
#pragma ivdep
#endif
for( iType i = loop_boundaries.start; i < loop_boundaries.end; i+=loop_boundaries.increment) {
ValueType tmp = ValueType();
lambda(i,tmp);
join(result,tmp);
}
init_result = result;
}
/** \brief Intra-thread vector parallel exclusive prefix sum. Executes lambda(iType i, ValueType & val, bool final)
* for each i=0..N-1.
*
* The range i=0..N-1 is mapped to all vector lanes in the thread and a scan operation is performed.
* Depending on the target execution space the operator might be called twice: once with final=false
* and once with final=true. When final==true val contains the prefix sum value. The contribution of this
* "i" needs to be added to val no matter whether final==true or not. In a serial execution
* (i.e. team_size==1) the operator is only called once with final==true. Scan_val will be set
* to the final sum value over all vector lanes.
* This functionality requires C++11 support.*/
template< typename iType, class FunctorType >
KOKKOS_INLINE_FUNCTION
void parallel_scan(const Impl::ThreadVectorRangeBoundariesStruct<iType,Impl::OpenMPTargetExecTeamMember >&
loop_boundaries, const FunctorType & lambda) {
typedef Kokkos::Impl::FunctorValueTraits< FunctorType , void > ValueTraits ;
typedef typename ValueTraits::value_type value_type ;
value_type scan_val = value_type();
#ifdef KOKKOS_HAVE_PRAGMA_IVDEP
#pragma ivdep
#endif
for( iType i = loop_boundaries.start; i < loop_boundaries.end; i+=loop_boundaries.increment) {
lambda(i,scan_val,true);
}
}
} // namespace Kokkos
namespace Kokkos {
template<class FunctorType>
KOKKOS_INLINE_FUNCTION
void single(const Impl::VectorSingleStruct<Impl::OpenMPTargetExecTeamMember>& single_struct, const FunctorType& lambda) {
lambda();
}
template<class FunctorType>
KOKKOS_INLINE_FUNCTION
void single(const Impl::ThreadSingleStruct<Impl::OpenMPTargetExecTeamMember>& single_struct, const FunctorType& lambda) {
if(single_struct.team_member.team_rank()==0) lambda();
}
template<class FunctorType, class ValueType>
KOKKOS_INLINE_FUNCTION
void single(const Impl::VectorSingleStruct<Impl::OpenMPTargetExecTeamMember>& single_struct, const FunctorType& lambda, ValueType& val) {
lambda(val);
}
template<class FunctorType, class ValueType>
KOKKOS_INLINE_FUNCTION
void single(const Impl::ThreadSingleStruct<Impl::OpenMPTargetExecTeamMember>& single_struct, const FunctorType& lambda, ValueType& val) {
if(single_struct.team_member.team_rank()==0) {
lambda(val);
}
single_struct.team_member.team_broadcast(val,0);
}
}
#endif /* #ifndef KOKKOS_OPENMPTARGETEXEC_HPP */
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