/usr/include/trilinos/Threads/Kokkos_ThreadsTeam.hpp is in libtrilinos-kokkos-dev 12.10.1-3.
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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_THREADSTEAM_HPP
#define KOKKOS_THREADSTEAM_HPP
#include <stdio.h>
#include <utility>
#include <impl/Kokkos_spinwait.hpp>
#include <impl/Kokkos_FunctorAdapter.hpp>
#include <Kokkos_Atomic.hpp>
//----------------------------------------------------------------------------
namespace Kokkos {
namespace Impl {
//----------------------------------------------------------------------------
template< class > struct ThreadsExecAdapter ;
//----------------------------------------------------------------------------
class ThreadsExecTeamMember {
private:
enum { TEAM_REDUCE_SIZE = 512 };
typedef Kokkos::Threads execution_space ;
typedef execution_space::scratch_memory_space space ;
ThreadsExec * const m_exec ;
ThreadsExec * const * m_team_base ; ///< Base for team fan-in
space m_team_shared ;
int m_team_shared_size ;
int m_team_size ;
int m_team_rank ;
int m_team_rank_rev ;
int m_league_size ;
int m_league_end ;
int m_league_rank ;
int m_chunk_size;
int m_league_chunk_end;
int m_invalid_thread;
int m_team_alloc;
inline
void set_team_shared()
{ new( & m_team_shared ) space( ((char *) (*m_team_base)->scratch_memory()) + TEAM_REDUCE_SIZE , m_team_shared_size ); }
public:
// Fan-in and wait until the matching fan-out is called.
// The root thread which does not wait will return true.
// All other threads will return false during the fan-out.
KOKKOS_INLINE_FUNCTION bool team_fan_in() const
{
int n , j ;
// Wait for fan-in threads
for ( n = 1 ; ( ! ( m_team_rank_rev & n ) ) && ( ( j = m_team_rank_rev + n ) < m_team_size ) ; n <<= 1 ) {
Impl::spinwait( m_team_base[j]->state() , ThreadsExec::Active );
}
// If not root then wait for release
if ( m_team_rank_rev ) {
m_exec->state() = ThreadsExec::Rendezvous ;
Impl::spinwait( m_exec->state() , ThreadsExec::Rendezvous );
}
return ! m_team_rank_rev ;
}
KOKKOS_INLINE_FUNCTION void team_fan_out() const
{
int n , j ;
for ( n = 1 ; ( ! ( m_team_rank_rev & n ) ) && ( ( j = m_team_rank_rev + n ) < m_team_size ) ; n <<= 1 ) {
m_team_base[j]->state() = ThreadsExec::Active ;
}
}
public:
KOKKOS_INLINE_FUNCTION static int team_reduce_size() { return TEAM_REDUCE_SIZE ; }
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
{
team_fan_in();
team_fan_out();
}
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 ;
if ( m_team_base ) {
type * const local_value = ((type*) m_team_base[0]->scratch_memory());
if(team_rank() == thread_id) *local_value = value;
memory_fence();
team_barrier();
value = *local_value;
}
#endif
}
template< typename Type >
KOKKOS_INLINE_FUNCTION Type team_reduce( const Type & value ) const
#if ! defined( KOKKOS_ACTIVE_EXECUTION_MEMORY_SPACE_HOST )
{ return Type(); }
#else
{
// Make sure there is enough scratch space:
typedef typename if_c< sizeof(Type) < TEAM_REDUCE_SIZE , Type , void >::type type ;
if ( 0 == m_exec ) return value ;
*((volatile type*) m_exec->scratch_memory() ) = value ;
memory_fence();
type & accum = *((type *) m_team_base[0]->scratch_memory() );
if ( team_fan_in() ) {
for ( int i = 1 ; i < m_team_size ; ++i ) {
accum += *((type *) m_team_base[i]->scratch_memory() );
}
memory_fence();
}
team_fan_out();
return accum ;
}
#endif
#ifdef KOKKOS_HAVE_CXX11
template< class ValueType, class JoinOp >
KOKKOS_INLINE_FUNCTION ValueType
team_reduce( const ValueType & value
, const JoinOp & op_in ) const
#if ! defined( KOKKOS_ACTIVE_EXECUTION_MEMORY_SPACE_HOST )
{ return ValueType(); }
#else
{
typedef ValueType value_type;
const JoinLambdaAdapter<value_type,JoinOp> op(op_in);
#endif
#else // KOKKOS_HAVE_CXX11
template< class JoinOp >
KOKKOS_INLINE_FUNCTION typename JoinOp::value_type
team_reduce( const typename JoinOp::value_type & value
, const JoinOp & op ) const
#if ! defined( KOKKOS_ACTIVE_EXECUTION_MEMORY_SPACE_HOST )
{ return typename JoinOp::value_type(); }
#else
{
typedef typename JoinOp::value_type value_type;
#endif
#endif // KOKKOS_HAVE_CXX11
#if defined( KOKKOS_ACTIVE_EXECUTION_MEMORY_SPACE_HOST )
// Make sure there is enough scratch space:
typedef typename if_c< sizeof(value_type) < TEAM_REDUCE_SIZE
, value_type , void >::type type ;
if ( 0 == m_exec ) return value ;
type * const local_value = ((type*) m_exec->scratch_memory());
// Set this thread's contribution
*local_value = value ;
// Fence to make sure the base team member has access:
memory_fence();
if ( team_fan_in() ) {
// The last thread to synchronize returns true, all other threads wait for team_fan_out()
type * const team_value = ((type*) m_team_base[0]->scratch_memory());
// Join to the team value:
for ( int i = 1 ; i < m_team_size ; ++i ) {
op.join( *team_value , *((type*) m_team_base[i]->scratch_memory()) );
}
// Team base thread may "lap" member threads so copy out to their local value.
for ( int i = 1 ; i < m_team_size ; ++i ) {
*((type*) m_team_base[i]->scratch_memory()) = *team_value ;
}
// Fence to make sure all team members have access
memory_fence();
}
team_fan_out();
// Value was changed by the team base
return *((type volatile const *) local_value);
}
#endif
/** \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
#if ! defined( KOKKOS_ACTIVE_EXECUTION_MEMORY_SPACE_HOST )
{ return ArgType(); }
#else
{
// Make sure there is enough scratch space:
typedef typename if_c< sizeof(ArgType) < TEAM_REDUCE_SIZE , ArgType , void >::type type ;
if ( 0 == m_exec ) return type(0);
volatile type * const work_value = ((type*) m_exec->scratch_memory());
*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_team_base[i]->scratch_memory());
accum += val ;
}
accum = atomic_fetch_add( global_accum , accum );
}
for ( int i = m_team_size ; i-- ; ) {
type & val = *((type*) m_team_base[i]->scratch_memory());
const type offset = accum ;
accum += val ;
val = offset ;
}
memory_fence();
}
team_fan_out();
return *work_value ;
}
#endif
/** \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 ArgType >
KOKKOS_INLINE_FUNCTION ArgType team_scan( const ArgType & value ) const
{ return this-> template team_scan<ArgType>( value , 0 ); }
//----------------------------------------
// Private for the driver
template< class ... Properties >
ThreadsExecTeamMember( Impl::ThreadsExec * exec
, const TeamPolicyInternal< Kokkos::Threads , Properties ... > & team
, const int shared_size )
: m_exec( exec )
, m_team_base(0)
, m_team_shared(0,0)
, m_team_shared_size( shared_size )
, m_team_size(team.team_size())
, m_team_rank(0)
, m_team_rank_rev(0)
, m_league_size(0)
, m_league_end(0)
, m_league_rank(0)
, m_chunk_size( team.chunk_size() )
, m_league_chunk_end(0)
, m_team_alloc( team.team_alloc())
{
if ( team.league_size() ) {
// Execution is using device-team interface:
const int pool_rank_rev = m_exec->pool_size() - ( m_exec->pool_rank() + 1 );
const int team_rank_rev = pool_rank_rev % team.team_alloc();
const size_t pool_league_size = m_exec->pool_size() / team.team_alloc() ;
const size_t pool_league_rank_rev = pool_rank_rev / team.team_alloc() ;
const size_t pool_league_rank = pool_league_size - ( pool_league_rank_rev + 1 );
const int pool_num_teams = m_exec->pool_size()/team.team_alloc();
const int chunk_size = team.chunk_size()>0?team.chunk_size():team.team_iter();
const int chunks_per_team = ( team.league_size() + chunk_size*pool_num_teams-1 ) / (chunk_size*pool_num_teams);
int league_iter_end = team.league_size() - pool_league_rank_rev * chunks_per_team * chunk_size;
int league_iter_begin = league_iter_end - chunks_per_team * chunk_size;
if (league_iter_begin < 0) league_iter_begin = 0;
if (league_iter_end>team.league_size()) league_iter_end = team.league_size();
if ((team.team_alloc()>m_team_size)?
(team_rank_rev >= m_team_size):
(m_exec->pool_size() - pool_num_teams*m_team_size > m_exec->pool_rank())
)
m_invalid_thread = 1;
else
m_invalid_thread = 0;
// May be using fewer threads per team than a multiple of threads per core,
// some threads will idle.
if ( team_rank_rev < team.team_size() && !m_invalid_thread) {
m_team_base = m_exec->pool_base() + team.team_alloc() * pool_league_rank_rev ;
m_team_size = team.team_size() ;
m_team_rank = team.team_size() - ( team_rank_rev + 1 );
m_team_rank_rev = team_rank_rev ;
m_league_size = team.league_size();
m_league_rank = ( team.league_size() * pool_league_rank ) / pool_league_size ;
m_league_end = ( team.league_size() * (pool_league_rank+1) ) / pool_league_size ;
set_team_shared();
}
if ( (m_team_rank_rev == 0) && (m_invalid_thread == 0) ) {
m_exec->set_work_range(m_league_rank,m_league_end,m_chunk_size);
m_exec->reset_steal_target(m_team_size);
}
if(std::is_same<typename TeamPolicyInternal<Kokkos::Threads, Properties ...>::schedule_type::type,Kokkos::Dynamic>::value) {
m_exec->barrier();
}
}
else
{ m_invalid_thread = 1; }
}
ThreadsExecTeamMember()
: m_exec(0)
, m_team_base(0)
, m_team_shared(0,0)
, m_team_shared_size(0)
, m_team_size(1)
, m_team_rank(0)
, m_team_rank_rev(0)
, m_league_size(1)
, m_league_end(0)
, m_league_rank(0)
, m_chunk_size(0)
, m_league_chunk_end(0)
, m_invalid_thread(0)
, m_team_alloc(0)
{}
inline
ThreadsExec & threads_exec_team_base() const { return m_team_base ? **m_team_base : *m_exec ; }
bool valid_static() const
{ return m_league_rank < m_league_end ; }
void next_static()
{
if ( m_league_rank < m_league_end ) {
team_barrier();
set_team_shared();
}
m_league_rank++;
}
bool valid_dynamic() {
if(m_invalid_thread)
return false;
if ((m_league_rank < m_league_chunk_end) && (m_league_rank < m_league_size)) {
return true;
}
if ( m_team_rank_rev == 0 ) {
m_team_base[0]->get_work_index(m_team_alloc);
}
team_barrier();
long work_index = m_team_base[0]->team_work_index();
m_league_rank = work_index * m_chunk_size;
m_league_chunk_end = (work_index +1 ) * m_chunk_size;
if(m_league_chunk_end > m_league_size) m_league_chunk_end = m_league_size;
if((m_league_rank>=0) && (m_league_rank < m_league_chunk_end))
return true;
return false;
}
void next_dynamic() {
if(m_invalid_thread)
return;
if ( m_league_rank < m_league_chunk_end ) {
team_barrier();
set_team_shared();
}
m_league_rank++;
}
void set_league_shmem( const int arg_league_rank
, const int arg_league_size
, const int arg_shmem_size
)
{
m_league_rank = arg_league_rank ;
m_league_size = arg_league_size ;
m_team_shared_size = arg_shmem_size ;
set_team_shared();
}
};
} /* namespace Impl */
} /* namespace Kokkos */
//----------------------------------------------------------------------------
//----------------------------------------------------------------------------
namespace Kokkos {
namespace Impl {
template< class ... Properties >
class TeamPolicyInternal< Kokkos::Threads , Properties ... >: public PolicyTraits<Properties ...>
{
private:
int m_league_size ;
int m_team_size ;
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 pool_size = traits::execution_space::thread_pool_size(0);
const int team_max = traits::execution_space::thread_pool_size(1);
const int team_grain = traits::execution_space::thread_pool_size(2);
m_league_size = league_size_request ;
m_team_size = team_size_request < team_max ?
team_size_request : team_max ;
// Round team size up to a multiple of 'team_gain'
const int team_size_grain = team_grain * ( ( m_team_size + team_grain - 1 ) / team_grain );
const int team_count = pool_size / team_size_grain ;
// Constraint : pool_size = m_team_alloc * team_count
m_team_alloc = pool_size / team_count ;
// Maxumum number of iterations each team will take:
m_team_iter = ( m_league_size + team_count - 1 ) / team_count ;
set_auto_chunk_size();
}
public:
//! Tag this class as a kokkos execution policy
//! 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_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 traits::execution_space::thread_pool_size(1); }
template< class FunctorType >
static int team_size_recommended( const FunctorType & )
{ return traits::execution_space::thread_pool_size(2); }
template< class FunctorType >
inline static
int team_size_recommended( const FunctorType &, const int& )
{ return traits::execution_space::thread_pool_size(2); }
//----------------------------------------
inline int team_size() const { return m_team_size ; }
inline int team_alloc() const { return m_team_alloc ; }
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] ;
}
inline int team_iter() const { return m_team_iter ; }
/** \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_league_size(0)
, m_team_size(0)
, m_team_alloc(0)
, m_team_scratch_size { 0 , 0 }
, m_thread_scratch_size { 0 , 0 }
, m_chunk_size(0)
{ init(league_size_request,team_size_request); (void) vector_length_request; }
/** \brief Specify league size, request team size */
TeamPolicyInternal( typename traits::execution_space &
, int league_size_request
, const Kokkos::AUTO_t & /* team_size_request */
, int /* vector_length_request */ = 1 )
: m_league_size(0)
, m_team_size(0)
, m_team_alloc(0)
, m_team_scratch_size { 0 , 0 }
, m_thread_scratch_size { 0 , 0 }
, m_chunk_size(0)
{ init(league_size_request,traits::execution_space::thread_pool_size(2)); }
TeamPolicyInternal( int league_size_request
, int team_size_request
, int /* vector_length_request */ = 1 )
: m_league_size(0)
, m_team_size(0)
, m_team_alloc(0)
, m_team_scratch_size { 0 , 0 }
, m_thread_scratch_size { 0 , 0 }
, m_chunk_size(0)
{ init(league_size_request,team_size_request); }
TeamPolicyInternal( int league_size_request
, const Kokkos::AUTO_t & /* team_size_request */
, int /* vector_length_request */ = 1 )
: m_league_size(0)
, m_team_size(0)
, m_team_alloc(0)
, m_team_scratch_size { 0 , 0 }
, m_thread_scratch_size { 0 , 0 }
, m_chunk_size(0)
{ init(league_size_request,traits::execution_space::thread_pool_size(2)); }
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;
}
/** \brief set per team scratch size for a specific level of the scratch hierarchy */
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;
};
/** \brief set per thread scratch size for a specific level of the scratch hierarchy */
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;
};
/** \brief set per thread and per team scratch size for a specific level of the scratch hierarchy */
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::ThreadsExecTeamMember member_type ;
friend class Impl::ThreadsExecTeamMember ;
};
} /*namespace Impl */
} /* namespace Kokkos */
namespace Kokkos {
template< typename iType >
KOKKOS_INLINE_FUNCTION
Impl::TeamThreadRangeBoundariesStruct< iType, Impl::ThreadsExecTeamMember >
TeamThreadRange( const Impl::ThreadsExecTeamMember& thread, const iType& count )
{
return Impl::TeamThreadRangeBoundariesStruct< iType, Impl::ThreadsExecTeamMember >( thread, count );
}
template< typename iType1, typename iType2 >
KOKKOS_INLINE_FUNCTION
Impl::TeamThreadRangeBoundariesStruct< typename std::common_type< iType1, iType2 >::type,
Impl::ThreadsExecTeamMember>
TeamThreadRange( const Impl::ThreadsExecTeamMember& thread, const iType1 & begin, const iType2 & end )
{
typedef typename std::common_type< iType1, iType2 >::type iType;
return Impl::TeamThreadRangeBoundariesStruct< iType, Impl::ThreadsExecTeamMember >( thread, iType(begin), iType(end) );
}
template<typename iType>
KOKKOS_INLINE_FUNCTION
Impl::ThreadVectorRangeBoundariesStruct<iType,Impl::ThreadsExecTeamMember >
ThreadVectorRange(const Impl::ThreadsExecTeamMember& thread, const iType& count) {
return Impl::ThreadVectorRangeBoundariesStruct<iType,Impl::ThreadsExecTeamMember >(thread,count);
}
KOKKOS_INLINE_FUNCTION
Impl::ThreadSingleStruct<Impl::ThreadsExecTeamMember> PerTeam(const Impl::ThreadsExecTeamMember& thread) {
return Impl::ThreadSingleStruct<Impl::ThreadsExecTeamMember>(thread);
}
KOKKOS_INLINE_FUNCTION
Impl::VectorSingleStruct<Impl::ThreadsExecTeamMember> PerThread(const Impl::ThreadsExecTeamMember& thread) {
return Impl::VectorSingleStruct<Impl::ThreadsExecTeamMember>(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::ThreadsExecTeamMember>& 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::ThreadsExecTeamMember>& 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>());
}
#if defined( KOKKOS_HAVE_CXX11 )
/** \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::ThreadsExecTeamMember>& 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,Impl::JoinLambdaAdapter<ValueType,JoinType>(join));
}
#endif /* #if defined( KOKKOS_HAVE_CXX11 ) */
} //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::ThreadsExecTeamMember >&
loop_boundaries, const Lambda& lambda) {
#ifdef KOKKOS_HAVE_PRAGMA_IVDEP
#pragma ivdep
#endif
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::ThreadsExecTeamMember >&
loop_boundaries, const Lambda & lambda, ValueType& result) {
result = ValueType();
#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);
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::ThreadsExecTeamMember >&
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::ThreadsExecTeamMember >&
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::ThreadsExecTeamMember>& single_struct, const FunctorType& lambda) {
lambda();
}
template<class FunctorType>
KOKKOS_INLINE_FUNCTION
void single(const Impl::ThreadSingleStruct<Impl::ThreadsExecTeamMember>& 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::ThreadsExecTeamMember>& single_struct, const FunctorType& lambda, ValueType& val) {
lambda(val);
}
template<class FunctorType, class ValueType>
KOKKOS_INLINE_FUNCTION
void single(const Impl::ThreadSingleStruct<Impl::ThreadsExecTeamMember>& 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 /* #define KOKKOS_THREADSTEAM_HPP */
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