This file is indexed.

/usr/include/trilinos/Threads/Kokkos_ThreadsTeam.hpp is in libtrilinos-kokkos-dev 12.10.1-3.

This file is owned by root:root, with mode 0o644.

The actual contents of the file can be viewed below.

  1
  2
  3
  4
  5
  6
  7
  8
  9
 10
 11
 12
 13
 14
 15
 16
 17
 18
 19
 20
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
/*
//@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 */