| 1 | /* | 
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| 2 | Copyright (c) 2005-2019 Intel Corporation | 
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| 3 |  | 
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| 4 | Licensed under the Apache License, Version 2.0 (the "License"); | 
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| 5 | you may not use this file except in compliance with the License. | 
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| 6 | You may obtain a copy of the License at | 
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| 7 |  | 
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| 8 | http://www.apache.org/licenses/LICENSE-2.0 | 
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| 9 |  | 
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| 10 | Unless required by applicable law or agreed to in writing, software | 
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| 11 | distributed under the License is distributed on an "AS IS" BASIS, | 
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| 12 | WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | 
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| 13 | See the License for the specific language governing permissions and | 
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| 14 | limitations under the License. | 
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| 15 | */ | 
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| 16 |  | 
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| 17 |  | 
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| 18 | #include "tbb/parallel_reduce.h" | 
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| 19 | #include "tbb/atomic.h" | 
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| 20 | #include "harness_assert.h" | 
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| 21 |  | 
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| 22 | using namespace std; | 
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| 23 |  | 
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| 24 | static tbb::atomic<long> ForkCount; | 
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| 25 | static tbb::atomic<long> FooBodyCount; | 
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| 26 |  | 
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| 27 | //! Class with public interface that is exactly minimal requirements for Range concept | 
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| 28 | class MinimalRange { | 
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| 29 | size_t begin, end; | 
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| 30 | friend class FooBody; | 
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| 31 | explicit MinimalRange( size_t i ) : begin(0), end(i) {} | 
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| 32 | friend void Flog( int nthread, bool inteference ); | 
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| 33 | public: | 
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| 34 | MinimalRange( MinimalRange& r, tbb::split ) : end(r.end) { | 
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| 35 | begin = r.end = (r.begin+r.end)/2; | 
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| 36 | } | 
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| 37 | bool is_divisible() const {return end-begin>=2;} | 
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| 38 | bool empty() const {return begin==end;} | 
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| 39 | }; | 
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| 40 |  | 
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| 41 | //! Class with public interface that is exactly minimal requirements for Body of a parallel_reduce | 
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| 42 | class FooBody { | 
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| 43 | private: | 
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| 44 | FooBody( const FooBody& );          // Deny access | 
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| 45 | void operator=( const FooBody& );   // Deny access | 
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| 46 | friend void Flog( int nthread, bool interference ); | 
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| 47 | //! Parent that created this body via split operation.  NULL if original body. | 
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| 48 | FooBody* parent; | 
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| 49 | //! Total number of index values processed by body and its children. | 
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| 50 | size_t sum; | 
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| 51 | //! Number of join operations done so far on this body and its children. | 
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| 52 | long join_count; | 
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| 53 | //! Range that has been processed so far by this body and its children. | 
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| 54 | size_t begin, end; | 
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| 55 | //! True if body has not yet been processed at least once by operator(). | 
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| 56 | bool is_new; | 
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| 57 | //! 1 if body was created by split; 0 if original body. | 
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| 58 | int forked; | 
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| 59 | FooBody() {++FooBodyCount;} | 
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| 60 | public: | 
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| 61 | ~FooBody() { | 
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| 62 | forked = 0xDEADBEEF; | 
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| 63 | sum=0xDEADBEEF; | 
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| 64 | join_count=0xDEADBEEF; | 
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| 65 | --FooBodyCount; | 
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| 66 | } | 
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| 67 | FooBody( FooBody& other, tbb::split ) { | 
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| 68 | ++FooBodyCount; | 
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| 69 | ++ForkCount; | 
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| 70 | sum = 0; | 
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| 71 | parent = &other; | 
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| 72 | join_count = 0; | 
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| 73 | is_new = true; | 
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| 74 | forked = 1; | 
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| 75 | } | 
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| 76 | void join( FooBody& s ) { | 
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| 77 | ASSERT( s.forked==1, NULL ); | 
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| 78 | ASSERT( this!=&s, NULL ); | 
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| 79 | ASSERT( this==s.parent, NULL ); | 
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| 80 | ASSERT( end==s.begin, NULL ); | 
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| 81 | end = s.end; | 
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| 82 | sum += s.sum; | 
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| 83 | join_count += s.join_count + 1; | 
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| 84 | s.forked = 2; | 
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| 85 | } | 
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| 86 | void operator()( const MinimalRange& r ) { | 
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| 87 | for( size_t k=r.begin; k<r.end; ++k ) | 
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| 88 | ++sum; | 
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| 89 | if( is_new ) { | 
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| 90 | is_new = false; | 
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| 91 | begin = r.begin; | 
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| 92 | } else | 
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| 93 | ASSERT( end==r.begin, NULL ); | 
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| 94 | end = r.end; | 
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| 95 | } | 
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| 96 | }; | 
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| 97 |  | 
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| 98 | #include <cstdio> | 
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| 99 | #include "harness.h" | 
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| 100 | #include "tbb/tick_count.h" | 
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| 101 |  | 
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| 102 | void Flog( int nthread, bool interference=false ) { | 
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| 103 | for (int mode = 0;  mode < 4; mode++) { | 
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| 104 | tbb::tick_count T0 = tbb::tick_count::now(); | 
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| 105 | long join_count = 0; | 
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| 106 | tbb::affinity_partitioner ap; | 
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| 107 | for( size_t i=0; i<=1000; ++i ) { | 
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| 108 | FooBody f; | 
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| 109 | f.sum = 0; | 
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| 110 | f.parent = NULL; | 
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| 111 | f.join_count = 0; | 
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| 112 | f.is_new = true; | 
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| 113 | f.forked = 0; | 
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| 114 | f.begin = ~size_t(0); | 
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| 115 | f.end = ~size_t(0); | 
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| 116 | ASSERT( FooBodyCount==1, NULL ); | 
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| 117 | switch (mode) { | 
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| 118 | case 0: | 
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| 119 | tbb::parallel_reduce( MinimalRange(i), f ); | 
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| 120 | break; | 
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| 121 | case 1: | 
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| 122 | tbb::parallel_reduce( MinimalRange(i), f, tbb::simple_partitioner() ); | 
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| 123 | break; | 
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| 124 | case 2: | 
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| 125 | tbb::parallel_reduce( MinimalRange(i), f, tbb::auto_partitioner() ); | 
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| 126 | break; | 
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| 127 | case 3: | 
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| 128 | tbb::parallel_reduce( MinimalRange(i), f, ap ); | 
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| 129 | break; | 
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| 130 | } | 
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| 131 | join_count += f.join_count; | 
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| 132 | ASSERT( FooBodyCount==1, NULL ); | 
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| 133 | ASSERT( f.sum==i, NULL ); | 
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| 134 | ASSERT( f.begin==(i==0 ? ~size_t(0) : 0), NULL ); | 
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| 135 | ASSERT( f.end==(i==0 ? ~size_t(0) : i), NULL ); | 
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| 136 | } | 
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| 137 | tbb::tick_count T1 = tbb::tick_count::now(); | 
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| 138 | REMARK( "time=%g join_count=%ld ForkCount=%ld nthread=%d%s\n", | 
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| 139 | (T1-T0).seconds(),join_count,long(ForkCount), nthread, interference ? " with interference": ""); | 
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| 140 | } | 
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| 141 | } | 
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| 142 |  | 
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| 143 | #include "tbb/blocked_range.h" | 
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| 144 |  | 
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| 145 | #if _MSC_VER | 
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| 146 | typedef tbb::internal::uint64_t ValueType; | 
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| 147 | #else | 
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| 148 | typedef uint64_t ValueType; | 
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| 149 | #endif | 
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| 150 |  | 
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| 151 | struct Sum { | 
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| 152 | template<typename T> | 
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| 153 | T operator() ( const T& v1, const T& v2 ) const { | 
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| 154 | return v1 + v2; | 
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| 155 | } | 
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| 156 | }; | 
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| 157 |  | 
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| 158 | struct Accumulator { | 
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| 159 | ValueType operator() ( const tbb::blocked_range<ValueType*>& r, ValueType value ) const { | 
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| 160 | for ( ValueType* pv = r.begin(); pv != r.end(); ++pv ) | 
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| 161 | value += *pv; | 
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| 162 | return value; | 
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| 163 | } | 
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| 164 | }; | 
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| 165 |  | 
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| 166 | class ParallelSumTester: public NoAssign { | 
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| 167 | public: | 
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| 168 | ParallelSumTester() : m_range(NULL, NULL) { | 
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| 169 | m_array = new ValueType[unsigned(N)]; | 
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| 170 | for ( ValueType i = 0; i < N; ++i ) | 
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| 171 | m_array[i] = i + 1; | 
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| 172 | m_range = tbb::blocked_range<ValueType*>( m_array, m_array + N ); | 
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| 173 | } | 
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| 174 | ~ParallelSumTester() { delete[] m_array; } | 
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| 175 | template<typename Partitioner> | 
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| 176 | void CheckParallelReduce() { | 
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| 177 | Partitioner partitioner; | 
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| 178 | ValueType r1 = tbb::parallel_reduce( m_range, I, Accumulator(), Sum(), partitioner ); | 
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| 179 | ASSERT( r1 == R, NULL ); | 
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| 180 | #if __TBB_CPP11_LAMBDAS_PRESENT | 
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| 181 | ValueType r2 = tbb::parallel_reduce( | 
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| 182 | m_range, I, | 
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| 183 | [](const tbb::blocked_range<ValueType*>& r, ValueType value) -> ValueType { | 
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| 184 | for ( const ValueType* pv = r.begin(); pv != r.end(); ++pv ) | 
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| 185 | value += *pv; | 
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| 186 | return value; | 
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| 187 | }, | 
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| 188 | Sum(), | 
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| 189 | partitioner | 
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| 190 | ); | 
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| 191 | ASSERT( r2 == R, NULL ); | 
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| 192 | #endif /* LAMBDAS */ | 
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| 193 | } | 
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| 194 | void CheckParallelReduceDefault() { | 
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| 195 | ValueType r1 = tbb::parallel_reduce( m_range, I, Accumulator(), Sum() ); | 
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| 196 | ASSERT( r1 == R, NULL ); | 
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| 197 | #if __TBB_CPP11_LAMBDAS_PRESENT | 
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| 198 | ValueType r2 = tbb::parallel_reduce( | 
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| 199 | m_range, I, | 
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| 200 | [](const tbb::blocked_range<ValueType*>& r, ValueType value) -> ValueType { | 
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| 201 | for ( const ValueType* pv = r.begin(); pv != r.end(); ++pv ) | 
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| 202 | value += *pv; | 
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| 203 | return value; | 
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| 204 | }, | 
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| 205 | Sum() | 
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| 206 | ); | 
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| 207 | ASSERT( r2 == R, NULL ); | 
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| 208 | #endif /* LAMBDAS */ | 
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| 209 | } | 
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| 210 | private: | 
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| 211 | ValueType* m_array; | 
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| 212 | tbb::blocked_range<ValueType*> m_range; | 
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| 213 | static const ValueType I, N, R; | 
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| 214 | }; | 
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| 215 |  | 
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| 216 | const ValueType ParallelSumTester::I = 0; | 
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| 217 | const ValueType ParallelSumTester::N = 1000000; | 
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| 218 | const ValueType ParallelSumTester::R = N * (N + 1) / 2; | 
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| 219 |  | 
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| 220 | void ParallelSum () { | 
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| 221 | ParallelSumTester pst; | 
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| 222 | pst.CheckParallelReduceDefault(); | 
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| 223 | pst.CheckParallelReduce<tbb::simple_partitioner>(); | 
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| 224 | pst.CheckParallelReduce<tbb::auto_partitioner>(); | 
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| 225 | pst.CheckParallelReduce<tbb::affinity_partitioner>(); | 
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| 226 | pst.CheckParallelReduce<tbb::static_partitioner>(); | 
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| 227 | } | 
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| 228 |  | 
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| 229 | #include "harness_concurrency_tracker.h" | 
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| 230 |  | 
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| 231 | class RotOp { | 
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| 232 | public: | 
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| 233 | typedef int Type; | 
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| 234 | int operator() ( int x, int i ) const { | 
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| 235 | return ( x<<1 ) ^ i; | 
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| 236 | } | 
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| 237 | int join( int x, int y ) const { | 
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| 238 | return operator()( x, y ); | 
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| 239 | } | 
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| 240 | }; | 
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| 241 |  | 
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| 242 | template <class Op> | 
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| 243 | struct ReduceBody { | 
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| 244 | typedef typename Op::Type result_type; | 
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| 245 | result_type my_value; | 
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| 246 |  | 
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| 247 | ReduceBody() : my_value() {} | 
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| 248 | ReduceBody( ReduceBody &, tbb::split ) : my_value() {} | 
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| 249 |  | 
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| 250 | void operator() ( const tbb::blocked_range<int>& r ) { | 
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| 251 | Harness::ConcurrencyTracker ct; | 
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| 252 | for ( int i = r.begin(); i != r.end(); ++i ) { | 
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| 253 | Op op; | 
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| 254 | my_value = op(my_value, i); | 
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| 255 | } | 
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| 256 | } | 
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| 257 |  | 
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| 258 | void join( const ReduceBody& y ) { | 
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| 259 | Op op; | 
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| 260 | my_value = op.join(my_value, y.my_value); | 
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| 261 | } | 
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| 262 | }; | 
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| 263 |  | 
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| 264 | //! Type-tag for automatic testing algorithm deduction | 
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| 265 | struct harness_default_partitioner {}; | 
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| 266 |  | 
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| 267 | template<typename Body, typename Partitioner> | 
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| 268 | struct parallel_deterministic_reduce_invoker { | 
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| 269 | template<typename Range> | 
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| 270 | static typename Body::result_type run( const Range& range ) { | 
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| 271 | Body body; | 
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| 272 | tbb::parallel_deterministic_reduce(range, body, Partitioner()); | 
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| 273 | return body.my_value; | 
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| 274 | } | 
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| 275 | }; | 
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| 276 |  | 
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| 277 | template<typename Body> | 
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| 278 | struct parallel_deterministic_reduce_invoker<Body, harness_default_partitioner> { | 
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| 279 | template<typename Range> | 
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| 280 | static typename Body::result_type run( const Range& range ) { | 
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| 281 | Body body; | 
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| 282 | tbb::parallel_deterministic_reduce(range, body); | 
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| 283 | return body.my_value; | 
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| 284 | } | 
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| 285 | }; | 
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| 286 |  | 
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| 287 | template<typename ResultType, typename Partitioner> | 
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| 288 | struct parallel_deterministic_reduce_lambda_invoker { | 
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| 289 | template<typename Range, typename Func, typename Reduction> | 
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| 290 | static ResultType run( const Range& range, Func f, Reduction r ) { | 
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| 291 | return tbb::parallel_deterministic_reduce(range, ResultType(), f, r, Partitioner()); | 
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| 292 | } | 
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| 293 | }; | 
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| 294 |  | 
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| 295 | template<typename ResultType> | 
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| 296 | struct parallel_deterministic_reduce_lambda_invoker<ResultType, harness_default_partitioner> { | 
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| 297 | template<typename Range, typename Func, typename Reduction> | 
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| 298 | static ResultType run(const Range& range, Func f, Reduction r) { | 
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| 299 | return tbb::parallel_deterministic_reduce(range, ResultType(), f, r); | 
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| 300 | } | 
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| 301 | }; | 
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| 302 |  | 
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| 303 | //! Define overloads of parallel_deterministic_reduce that accept "undesired" types of partitioners | 
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| 304 | namespace unsupported { | 
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| 305 |  | 
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| 306 | template<typename Range, typename Body> | 
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| 307 | void parallel_deterministic_reduce(const Range&, Body&, const tbb::auto_partitioner&) { } | 
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| 308 |  | 
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| 309 | template<typename Range, typename Body> | 
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| 310 | void parallel_deterministic_reduce(const Range&, Body&, tbb::affinity_partitioner&) { } | 
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| 311 |  | 
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| 312 | template<typename Range, typename Value, typename RealBody, typename Reduction> | 
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| 313 | Value parallel_deterministic_reduce(const Range& , const Value& identity, const RealBody& , const Reduction& , const tbb::auto_partitioner&) { | 
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| 314 | return identity; | 
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| 315 | } | 
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| 316 |  | 
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| 317 | template<typename Range, typename Value, typename RealBody, typename Reduction> | 
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| 318 | Value parallel_deterministic_reduce(const Range& , const Value& identity, const RealBody& , const Reduction& , tbb::affinity_partitioner&) { | 
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| 319 | return identity; | 
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| 320 | } | 
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| 321 |  | 
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| 322 | } | 
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| 323 |  | 
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| 324 | struct Body { | 
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| 325 | float value; | 
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| 326 | Body() : value(0) {} | 
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| 327 | Body(Body&, tbb::split) { value = 0; } | 
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| 328 | void operator()(const tbb::blocked_range<int>&) {} | 
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| 329 | void join(Body&) {} | 
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| 330 | }; | 
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| 331 |  | 
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| 332 | //! Check that other types of partitioners are not supported (auto, affinity) | 
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| 333 | //! In the case of "unsupported" API unexpectedly sneaking into namespace tbb, | 
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| 334 | //! this test should result in a compilation error due to overload resolution ambiguity | 
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| 335 | static void TestUnsupportedPartitioners() { | 
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| 336 | using namespace tbb; | 
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| 337 | using namespace unsupported; | 
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| 338 | Body body; | 
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| 339 | parallel_deterministic_reduce(blocked_range<int>(0, 10), body, tbb::auto_partitioner()); | 
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| 340 |  | 
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| 341 | tbb::affinity_partitioner ap; | 
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| 342 | parallel_deterministic_reduce(blocked_range<int>(0, 10), body, ap); | 
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| 343 |  | 
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| 344 | #if __TBB_CPP11_LAMBDAS_PRESENT | 
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| 345 | parallel_deterministic_reduce( | 
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| 346 | blocked_range<int>(0, 10), | 
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| 347 | 0, | 
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| 348 | [](const blocked_range<int>&, int init)->int { | 
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| 349 | return init; | 
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| 350 | }, | 
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| 351 | [](int x, int y)->int { | 
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| 352 | return x + y; | 
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| 353 | }, | 
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| 354 | tbb::auto_partitioner() | 
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| 355 | ); | 
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| 356 | parallel_deterministic_reduce( | 
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| 357 | blocked_range<int>(0, 10), | 
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| 358 | 0, | 
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| 359 | [](const blocked_range<int>&, int init)->int { | 
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| 360 | return init; | 
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| 361 | }, | 
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| 362 | [](int x, int y)->int { | 
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| 363 | return x + y; | 
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| 364 | }, | 
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| 365 | ap | 
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| 366 | ); | 
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| 367 | #endif /* LAMBDAS */ | 
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| 368 | } | 
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| 369 |  | 
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| 370 | template <class Partitioner> | 
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| 371 | void TestDeterministicReductionFor() { | 
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| 372 | const int N = 1000; | 
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| 373 | const tbb::blocked_range<int> range(0, N); | 
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| 374 | typedef ReduceBody<RotOp> BodyType; | 
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| 375 | BodyType::result_type R1 = | 
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| 376 | parallel_deterministic_reduce_invoker<BodyType, Partitioner>::run(range); | 
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| 377 | for ( int i=0; i<100; ++i ) { | 
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| 378 | BodyType::result_type R2 = | 
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| 379 | parallel_deterministic_reduce_invoker<BodyType, Partitioner>::run(range); | 
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| 380 | ASSERT( R1 == R2, "parallel_deterministic_reduce behaves differently from run to run"); | 
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| 381 | #if __TBB_CPP11_LAMBDAS_PRESENT | 
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| 382 | typedef RotOp::Type Type; | 
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| 383 | Type R3 = parallel_deterministic_reduce_lambda_invoker<Type, Partitioner>::run( | 
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| 384 | range, | 
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| 385 | [](const tbb::blocked_range<int>& br, Type value) -> Type { | 
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| 386 | Harness::ConcurrencyTracker ct; | 
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| 387 | for ( int ii = br.begin(); ii != br.end(); ++ii ) { | 
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| 388 | RotOp op; | 
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| 389 | value = op(value, ii); | 
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| 390 | } | 
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| 391 | return value; | 
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| 392 | }, | 
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| 393 | [](const Type& v1, const Type& v2) -> Type { | 
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| 394 | RotOp op; | 
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| 395 | return op.join(v1,v2); | 
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| 396 | } | 
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| 397 | ); | 
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| 398 | ASSERT( R1 == R3, "lambda-based parallel_deterministic_reduce behaves differently from run to run"); | 
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| 399 | #endif /* LAMBDAS */ | 
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| 400 | } | 
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| 401 | } | 
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| 402 |  | 
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| 403 | void TestDeterministicReduction () { | 
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| 404 | TestDeterministicReductionFor<tbb::simple_partitioner>(); | 
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| 405 | TestDeterministicReductionFor<tbb::static_partitioner>(); | 
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| 406 | TestDeterministicReductionFor<harness_default_partitioner>(); | 
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| 407 | ASSERT_WARNING((Harness::ConcurrencyTracker::PeakParallelism() > 1), "no parallel execution\n"); | 
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| 408 | } | 
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| 409 |  | 
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| 410 | #include "tbb/task_scheduler_init.h" | 
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| 411 | #include "harness_cpu.h" | 
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| 412 | #include "test_partitioner.h" | 
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| 413 |  | 
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| 414 | namespace interaction_with_range_and_partitioner { | 
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| 415 |  | 
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| 416 | // Test checks compatibility of parallel_reduce algorithm with various range implementations | 
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| 417 |  | 
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| 418 | void test() { | 
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| 419 | using namespace test_partitioner_utils::interaction_with_range_and_partitioner; | 
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| 420 |  | 
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| 421 | test_partitioner_utils::SimpleReduceBody body; | 
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| 422 | tbb::affinity_partitioner ap; | 
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| 423 |  | 
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| 424 | parallel_reduce(Range1(/*assert_in_split*/ true, /*assert_in_proportional_split*/ false), body, ap); | 
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| 425 | parallel_reduce(Range2(true, false), body, ap); | 
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| 426 | parallel_reduce(Range3(true, false), body, ap); | 
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| 427 | parallel_reduce(Range4(false, true), body, ap); | 
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| 428 | parallel_reduce(Range5(false, true), body, ap); | 
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| 429 | parallel_reduce(Range6(false, true), body, ap); | 
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| 430 |  | 
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| 431 | parallel_reduce(Range1(/*assert_in_split*/ true, /*assert_in_proportional_split*/ false), | 
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| 432 | body, tbb::static_partitioner()); | 
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| 433 | parallel_reduce(Range2(true, false), body, tbb::static_partitioner()); | 
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| 434 | parallel_reduce(Range3(true, false), body, tbb::static_partitioner()); | 
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| 435 | parallel_reduce(Range4(false, true), body, tbb::static_partitioner()); | 
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| 436 | parallel_reduce(Range5(false, true), body, tbb::static_partitioner()); | 
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| 437 | parallel_reduce(Range6(false, true), body, tbb::static_partitioner()); | 
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| 438 |  | 
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| 439 | parallel_reduce(Range1(/*assert_in_split*/ false, /*assert_in_proportional_split*/ true), | 
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| 440 | body, tbb::simple_partitioner()); | 
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| 441 | parallel_reduce(Range2(false, true), body, tbb::simple_partitioner()); | 
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| 442 | parallel_reduce(Range3(false, true), body, tbb::simple_partitioner()); | 
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| 443 | parallel_reduce(Range4(false, true), body, tbb::simple_partitioner()); | 
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| 444 | parallel_reduce(Range5(false, true), body, tbb::simple_partitioner()); | 
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| 445 | parallel_reduce(Range6(false, true), body, tbb::simple_partitioner()); | 
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| 446 |  | 
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| 447 | parallel_reduce(Range1(/*assert_in_split*/ false, /*assert_in_proportional_split*/ true), | 
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| 448 | body, tbb::auto_partitioner()); | 
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| 449 | parallel_reduce(Range2(false, true), body, tbb::auto_partitioner()); | 
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| 450 | parallel_reduce(Range3(false, true), body, tbb::auto_partitioner()); | 
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| 451 | parallel_reduce(Range4(false, true), body, tbb::auto_partitioner()); | 
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| 452 | parallel_reduce(Range5(false, true), body, tbb::auto_partitioner()); | 
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| 453 | parallel_reduce(Range6(false, true), body, tbb::auto_partitioner()); | 
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| 454 |  | 
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| 455 | parallel_deterministic_reduce(Range1(/*assert_in_split*/true, /*assert_in_proportional_split*/ false), | 
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| 456 | body, tbb::static_partitioner()); | 
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| 457 | parallel_deterministic_reduce(Range2(true, false), body, tbb::static_partitioner()); | 
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| 458 | parallel_deterministic_reduce(Range3(true, false), body, tbb::static_partitioner()); | 
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| 459 | parallel_deterministic_reduce(Range4(false, true), body, tbb::static_partitioner()); | 
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| 460 | parallel_deterministic_reduce(Range5(false, true), body, tbb::static_partitioner()); | 
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| 461 | parallel_deterministic_reduce(Range6(false, true), body, tbb::static_partitioner()); | 
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| 462 |  | 
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| 463 | parallel_deterministic_reduce(Range1(/*assert_in_split*/false, /*assert_in_proportional_split*/ true), | 
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| 464 | body, tbb::simple_partitioner()); | 
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| 465 | parallel_deterministic_reduce(Range2(false, true), body, tbb::simple_partitioner()); | 
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| 466 | parallel_deterministic_reduce(Range3(false, true), body, tbb::simple_partitioner()); | 
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| 467 | parallel_deterministic_reduce(Range4(false, true), body, tbb::simple_partitioner()); | 
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| 468 | parallel_deterministic_reduce(Range5(false, true), body, tbb::simple_partitioner()); | 
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| 469 | parallel_deterministic_reduce(Range6(false, true), body, tbb::simple_partitioner()); | 
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| 470 | } | 
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| 471 |  | 
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| 472 | } // interaction_with_range_and_partitioner | 
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| 473 |  | 
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| 474 | int TestMain () { | 
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| 475 | TestUnsupportedPartitioners(); | 
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| 476 | if( MinThread<0 ) { | 
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| 477 | REPORT( "Usage: nthread must be positive\n"); | 
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| 478 | exit(1); | 
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| 479 | } | 
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| 480 | for( int p=MinThread; p<=MaxThread; ++p ) { | 
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| 481 | tbb::task_scheduler_init init( p ); | 
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| 482 | Flog(p); | 
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| 483 | ParallelSum(); | 
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| 484 | if ( p>=2 ) | 
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| 485 | TestDeterministicReduction(); | 
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| 486 | // Test that all workers sleep when no work | 
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| 487 | TestCPUUserTime(p); | 
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| 488 | } | 
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| 489 | interaction_with_range_and_partitioner::test(); | 
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| 490 | return Harness::Done; | 
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| 491 | } | 
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| 492 |  | 
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