File: TestStdAlgorithmsTeamUnique.cpp

package info (click to toggle)
kokkos 5.0.1-1
  • links: PTS, VCS
  • area: main
  • in suites: experimental
  • size: 15,140 kB
  • sloc: cpp: 225,293; sh: 1,250; python: 78; makefile: 16; fortran: 4; ansic: 2
file content (158 lines) | stat: -rw-r--r-- 6,336 bytes parent folder | download
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
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
// SPDX-FileCopyrightText: Copyright Contributors to the Kokkos project

#include <TestStdAlgorithmsCommon.hpp>
#include <algorithm>

namespace Test {
namespace stdalgos {
namespace TeamUniqueDefaultPredicate {

namespace KE = Kokkos::Experimental;

template <class ViewType, class DistancesViewType, class IntraTeamSentinelView>
struct TestFunctorA {
  ViewType m_view;
  DistancesViewType m_distancesView;
  IntraTeamSentinelView m_intraTeamSentinelView;
  int m_apiPick;

  TestFunctorA(const ViewType view, const DistancesViewType distancesView,
               const IntraTeamSentinelView intraTeamSentinelView, int apiPick)
      : m_view(view),
        m_distancesView(distancesView),
        m_intraTeamSentinelView(intraTeamSentinelView),
        m_apiPick(apiPick) {}

  template <class MemberType>
  KOKKOS_INLINE_FUNCTION void operator()(const MemberType& member) const {
    const auto myRowIndex = member.league_rank();
    auto myRowView        = Kokkos::subview(m_view, myRowIndex, Kokkos::ALL());
    ptrdiff_t resultDist  = 0;

    if (m_apiPick == 0) {
      auto it    = KE::unique(member, KE::begin(myRowView), KE::end(myRowView));
      resultDist = KE::distance(KE::begin(myRowView), it);
      Kokkos::single(Kokkos::PerTeam(member), [=, *this]() {
        m_distancesView(myRowIndex) = resultDist;
      });
    } else if (m_apiPick == 1) {
      auto it    = KE::unique(member, myRowView);
      resultDist = KE::distance(KE::begin(myRowView), it);
      Kokkos::single(Kokkos::PerTeam(member), [=, *this]() {
        m_distancesView(myRowIndex) = resultDist;
      });
    } else if (m_apiPick == 2) {
      using value_type = typename ViewType::value_type;
      auto it    = KE::unique(member, KE::begin(myRowView), KE::end(myRowView),
                              CustomEqualityComparator<value_type>{});
      resultDist = KE::distance(KE::begin(myRowView), it);
      Kokkos::single(Kokkos::PerTeam(member), [=, *this]() {
        m_distancesView(myRowIndex) = resultDist;
      });
    } else if (m_apiPick == 3) {
      using value_type = typename ViewType::value_type;
      auto it =
          KE::unique(member, myRowView, CustomEqualityComparator<value_type>{});
      resultDist = KE::distance(KE::begin(myRowView), it);
      Kokkos::single(Kokkos::PerTeam(member), [=, *this]() {
        m_distancesView(myRowIndex) = resultDist;
      });
    }

    // store result of checking if all members have their local
    // values matching the one stored in m_distancesView
    member.team_barrier();
    const bool intraTeamCheck = team_members_have_matching_result(
        member, resultDist, m_distancesView(myRowIndex));
    Kokkos::single(Kokkos::PerTeam(member), [=, *this]() {
      m_intraTeamSentinelView(myRowIndex) = intraTeamCheck;
    });
  }
};

template <class LayoutTag, class ValueType>
void test_A(std::size_t numTeams, std::size_t numCols, int apiId) {
  /* description:
     team-level KE::unique on a rank-2 view where
     data is filled randomly such that we have several subsets
     of consecutive equal elements. Use one team per row.
   */

  // -----------------------------------------------
  // prepare data
  // -----------------------------------------------
  // create a view in the memory space associated with default exespace
  // with as many rows as the number of teams and fill it with random
  // values from a range that is tight enough that there is a high likelihood
  // of having several consecutive subsets of equal elements
  auto [dataView, cloneOfDataViewBeforeOp_h] =
      create_random_view_and_host_clone(
          LayoutTag{}, numTeams, numCols,
          Kokkos::pair<ValueType, ValueType>{121, 153}, "dataView");

  // -----------------------------------------------
  // launch kokkos kernel
  // -----------------------------------------------
  using space_t = Kokkos::DefaultExecutionSpace;
  Kokkos::TeamPolicy<space_t> policy(numTeams, Kokkos::AUTO());

  // each team stores the distance of the returned iterator from the
  // beginning of the interval that team operates on and then we check
  // that these distances match the expectation
  Kokkos::View<std::size_t*> distancesView("distancesView", numTeams);
  // sentinel to check if all members of the team compute the same result
  Kokkos::View<bool*> intraTeamSentinelView("intraTeamSameResult", numTeams);

  // use CTAD for functor
  TestFunctorA fnc(dataView, distancesView, intraTeamSentinelView, apiId);
  Kokkos::parallel_for(policy, fnc);

  // -----------------------------------------------
  // run std algo and check
  // -----------------------------------------------
  // here I can use cloneOfDataViewBeforeOp_h to run std algo on
  // since that contains a valid copy of the data
  auto distancesView_h         = create_host_space_copy(distancesView);
  auto intraTeamSentinelView_h = create_host_space_copy(intraTeamSentinelView);

  for (std::size_t i = 0; i < cloneOfDataViewBeforeOp_h.extent(0); ++i) {
    auto myRow = Kokkos::subview(cloneOfDataViewBeforeOp_h, i, Kokkos::ALL());

    std::size_t stdDistance = 0;
    if (apiId <= 1) {
      auto it     = std::unique(KE::begin(myRow), KE::end(myRow));
      stdDistance = KE::distance(KE::begin(myRow), it);
    } else {
      auto it     = std::unique(KE::begin(myRow), KE::end(myRow),
                                CustomEqualityComparator<value_type>{});
      stdDistance = KE::distance(KE::begin(myRow), it);
    }
    ASSERT_EQ(stdDistance, distancesView_h(i));
    ASSERT_TRUE(intraTeamSentinelView_h(i));
  }

  auto dataViewAfterOp_h = create_host_space_copy(dataView);
  expect_equal_host_views(cloneOfDataViewBeforeOp_h, dataViewAfterOp_h);
}

template <class LayoutTag, class ValueType>
void run_all_scenarios() {
  for (int numTeams : teamSizesToTest) {
    for (const auto& numCols : {0, 1, 2, 13, 101, 1444, 11113}) {
      for (int apiId : {0, 1}) {
        test_A<LayoutTag, ValueType>(numTeams, numCols, apiId);
      }
    }
  }
}

TEST(std_algorithms_unique_team_test, test_default_predicate) {
  run_all_scenarios<DynamicTag, int>();
  run_all_scenarios<StridedTwoRowsTag, int>();
  run_all_scenarios<StridedThreeRowsTag, int>();
}

}  // namespace TeamUniqueDefaultPredicate
}  // namespace stdalgos
}  // namespace Test