| 1 | // Copyright 2009-2021 Intel Corporation |
| 2 | // SPDX-License-Identifier: Apache-2.0 |
| 3 | |
| 4 | #pragma once |
| 5 | |
| 6 | #include "parallel_for.h" |
| 7 | |
| 8 | namespace embree |
| 9 | { |
| 10 | template<typename Index, typename Value, typename Func, typename Reduction> |
| 11 | __forceinline Value sequential_reduce( const Index first, const Index last, const Value& identity, const Func& func, const Reduction& reduction ) |
| 12 | { |
| 13 | return func(range<Index>(first,last)); |
| 14 | } |
| 15 | |
| 16 | template<typename Index, typename Value, typename Func, typename Reduction> |
| 17 | __forceinline Value sequential_reduce( const Index first, const Index last, const Index minStepSize, const Value& identity, const Func& func, const Reduction& reduction ) |
| 18 | { |
| 19 | return func(range<Index>(first,last)); |
| 20 | } |
| 21 | |
| 22 | template<typename Index, typename Value, typename Func, typename Reduction> |
| 23 | __noinline Value parallel_reduce_internal( Index taskCount, const Index first, const Index last, const Index minStepSize, const Value& identity, const Func& func, const Reduction& reduction ) |
| 24 | { |
| 25 | const Index maxTasks = 512; |
| 26 | const Index threadCount = (Index) TaskScheduler::threadCount(); |
| 27 | taskCount = min(taskCount,threadCount,maxTasks); |
| 28 | |
| 29 | /* parallel invocation of all tasks */ |
| 30 | dynamic_large_stack_array(Value,values,taskCount,8192); // consumes at most 8192 bytes on the stack |
| 31 | parallel_for(taskCount, [&](const Index taskIndex) { |
| 32 | const Index k0 = first+(taskIndex+0)*(last-first)/taskCount; |
| 33 | const Index k1 = first+(taskIndex+1)*(last-first)/taskCount; |
| 34 | values[taskIndex] = func(range<Index>(k0,k1)); |
| 35 | }); |
| 36 | |
| 37 | /* perform reduction over all tasks */ |
| 38 | Value v = identity; |
| 39 | for (Index i=0; i<taskCount; i++) v = reduction(v,values[i]); |
| 40 | return v; |
| 41 | } |
| 42 | |
| 43 | template<typename Index, typename Value, typename Func, typename Reduction> |
| 44 | __forceinline Value parallel_reduce( const Index first, const Index last, const Index minStepSize, const Value& identity, const Func& func, const Reduction& reduction ) |
| 45 | { |
| 46 | #if defined(TASKING_INTERNAL) |
| 47 | |
| 48 | /* fast path for small number of iterations */ |
| 49 | Index taskCount = (last-first+minStepSize-1)/minStepSize; |
| 50 | if (likely(taskCount == 1)) { |
| 51 | return func(range<Index>(first,last)); |
| 52 | } |
| 53 | return parallel_reduce_internal(taskCount,first,last,minStepSize,identity,func,reduction); |
| 54 | |
| 55 | #elif defined(TASKING_TBB) |
| 56 | #if TBB_INTERFACE_VERSION >= 12002 |
| 57 | tbb::task_group_context context; |
| 58 | const Value v = tbb::parallel_reduce(tbb::blocked_range<Index>(first,last,minStepSize),identity, |
| 59 | [&](const tbb::blocked_range<Index>& r, const Value& start) { return reduction(start,func(range<Index>(r.begin(),r.end()))); }, |
| 60 | reduction,context); |
| 61 | // -- GODOT start -- |
| 62 | // if (context.is_group_execution_cancelled()) |
| 63 | // throw std::runtime_error("task cancelled"); |
| 64 | // -- GODOT end -- |
| 65 | return v; |
| 66 | #else |
| 67 | const Value v = tbb::parallel_reduce(tbb::blocked_range<Index>(first,last,minStepSize),identity, |
| 68 | [&](const tbb::blocked_range<Index>& r, const Value& start) { return reduction(start,func(range<Index>(r.begin(),r.end()))); }, |
| 69 | reduction); |
| 70 | // -- GODOT start -- |
| 71 | // if (tbb::task::self().is_cancelled()) |
| 72 | // throw std::runtime_error("task cancelled"); |
| 73 | // -- GODOT end -- |
| 74 | return v; |
| 75 | #endif |
| 76 | #else // TASKING_PPL |
| 77 | struct AlignedValue |
| 78 | { |
| 79 | char storage[__alignof(Value)+sizeof(Value)]; |
| 80 | static uintptr_t alignUp(uintptr_t p, size_t a) { return p + (~(p - 1) % a); }; |
| 81 | Value* getValuePtr() { return reinterpret_cast<Value*>(alignUp(uintptr_t(storage), __alignof(Value))); } |
| 82 | const Value* getValuePtr() const { return reinterpret_cast<Value*>(alignUp(uintptr_t(storage), __alignof(Value))); } |
| 83 | AlignedValue(const Value& v) { new(getValuePtr()) Value(v); } |
| 84 | AlignedValue(const AlignedValue& v) { new(getValuePtr()) Value(*v.getValuePtr()); } |
| 85 | AlignedValue(const AlignedValue&& v) { new(getValuePtr()) Value(*v.getValuePtr()); }; |
| 86 | AlignedValue& operator = (const AlignedValue& v) { *getValuePtr() = *v.getValuePtr(); return *this; }; |
| 87 | AlignedValue& operator = (const AlignedValue&& v) { *getValuePtr() = *v.getValuePtr(); return *this; }; |
| 88 | operator Value() const { return *getValuePtr(); } |
| 89 | }; |
| 90 | |
| 91 | struct Iterator_Index |
| 92 | { |
| 93 | Index v; |
| 94 | typedef std::forward_iterator_tag iterator_category; |
| 95 | typedef AlignedValue value_type; |
| 96 | typedef Index difference_type; |
| 97 | typedef Index distance_type; |
| 98 | typedef AlignedValue* pointer; |
| 99 | typedef AlignedValue& reference; |
| 100 | __forceinline Iterator_Index() {} |
| 101 | __forceinline Iterator_Index(Index v) : v(v) {} |
| 102 | __forceinline bool operator== (Iterator_Index other) { return v == other.v; } |
| 103 | __forceinline bool operator!= (Iterator_Index other) { return v != other.v; } |
| 104 | __forceinline Iterator_Index operator++() { return Iterator_Index(++v); } |
| 105 | __forceinline Iterator_Index operator++(int) { return Iterator_Index(v++); } |
| 106 | }; |
| 107 | |
| 108 | auto range_reduction = [&](Iterator_Index begin, Iterator_Index end, const AlignedValue& start) { |
| 109 | assert(begin.v < end.v); |
| 110 | return reduction(start, func(range<Index>(begin.v, end.v))); |
| 111 | }; |
| 112 | const Value v = concurrency::parallel_reduce(Iterator_Index(first), Iterator_Index(last), AlignedValue(identity), range_reduction, reduction); |
| 113 | return v; |
| 114 | #endif |
| 115 | } |
| 116 | |
| 117 | template<typename Index, typename Value, typename Func, typename Reduction> |
| 118 | __forceinline Value parallel_reduce( const Index first, const Index last, const Index minStepSize, const Index parallel_threshold, const Value& identity, const Func& func, const Reduction& reduction ) |
| 119 | { |
| 120 | if (likely(last-first < parallel_threshold)) { |
| 121 | return func(range<Index>(first,last)); |
| 122 | } else { |
| 123 | return parallel_reduce(first,last,minStepSize,identity,func,reduction); |
| 124 | } |
| 125 | } |
| 126 | |
| 127 | template<typename Index, typename Value, typename Func, typename Reduction> |
| 128 | __forceinline Value parallel_reduce( const range<Index> range, const Index minStepSize, const Index parallel_threshold, const Value& identity, const Func& func, const Reduction& reduction ) |
| 129 | { |
| 130 | return parallel_reduce(range.begin(),range.end(),minStepSize,parallel_threshold,identity,func,reduction); |
| 131 | } |
| 132 | |
| 133 | template<typename Index, typename Value, typename Func, typename Reduction> |
| 134 | __forceinline Value parallel_reduce( const Index first, const Index last, const Value& identity, const Func& func, const Reduction& reduction ) |
| 135 | { |
| 136 | auto funcr = [&] ( const range<Index> r ) { |
| 137 | Value v = identity; |
| 138 | for (Index i=r.begin(); i<r.end(); i++) |
| 139 | v = reduction(v,func(i)); |
| 140 | return v; |
| 141 | }; |
| 142 | return parallel_reduce(first,last,Index(1),identity,funcr,reduction); |
| 143 | } |
| 144 | |
| 145 | template<typename Index, typename Value, typename Func, typename Reduction> |
| 146 | __forceinline Value parallel_reduce( const range<Index> range, const Value& identity, const Func& func, const Reduction& reduction ) |
| 147 | { |
| 148 | return parallel_reduce(range.begin(),range.end(),Index(1),identity,func,reduction); |
| 149 | } |
| 150 | } |
| 151 | |