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ANSLibs/OpenVINO/runtime/include/openvino/core/parallel.hpp

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// Copyright (C) 2018-2025 Intel Corporation
// SPDX-License-Identifier: Apache-2.0
//
/**
* @brief Contains declarations and definitions for sequential and multi-threading implementations.
*
* Multi-threading support is implemented in two variants: using the Threading Building Blocks library and OpenMP*
* product. To build a particular implementation, use the corresponding identifier: OV_THREAD_TBB, OV_THREAD_TBB_AUTO,
* OV_THREAD_OMP or OV_THREAD_SEQ.
*
* @file parallel.hpp
*/
#pragma once
#include <cstddef>
#include <type_traits>
#define OV_THREAD_TBB 0
#define OV_THREAD_OMP 1
#define OV_THREAD_SEQ 2
#define OV_THREAD_TBB_AUTO 3
#if (OV_THREAD == OV_THREAD_TBB || OV_THREAD == OV_THREAD_TBB_AUTO)
# ifndef NOMINMAX
# define NOMINMAX
# endif
# ifndef TBB_PREVIEW_LOCAL_OBSERVER
# define TBB_PREVIEW_LOCAL_OBSERVER 1
# endif
# ifndef TBB_PREVIEW_WAITING_FOR_WORKERS
# define TBB_PREVIEW_WAITING_FOR_WORKERS 1
# endif
# ifndef TBB_PREVIEW_NUMA_SUPPORT
# define TBB_PREVIEW_NUMA_SUPPORT 1
# endif
# ifndef TBB_PREVIEW_TASK_ARENA_CONSTRAINTS_EXTENSION
# define TBB_PREVIEW_TASK_ARENA_CONSTRAINTS_EXTENSION 1
# endif
# include "tbb/blocked_range.h"
# include "tbb/blocked_range2d.h"
# include "tbb/blocked_range3d.h"
# include "tbb/parallel_for.h"
# include "tbb/parallel_reduce.h"
# include "tbb/parallel_sort.h"
# include "tbb/task_arena.h"
# include "tbb/task_scheduler_observer.h"
inline int parallel_get_max_threads() {
return tbb::this_task_arena::max_concurrency();
}
inline int parallel_get_num_threads() {
return parallel_get_max_threads();
}
inline int parallel_get_thread_num() {
return tbb::this_task_arena::current_thread_index();
}
inline void parallel_set_num_threads(int) {
return;
}
inline int parallel_get_env_threads() {
return 0;
}
inline void parallel_set_max_nested_levels(int levels) {
return;
}
# if OV_THREAD == OV_THREAD_TBB
# define PARTITIONING , tbb::static_partitioner()
// The TBB version less than 2018u1 has no static_partitioner argument for
// tbb::parallel_deterministic_reduce. So will fallback to non deterministic version.
# if (TBB_INTERFACE_VERSION >= 10001)
# define _TBB_REDUCE_FUNC tbb::parallel_deterministic_reduce
# else
# define _TBB_REDUCE_FUNC tbb::parallel_reduce
# endif
# else
# define PARTITIONING
# endif
#elif OV_THREAD == OV_THREAD_OMP
# include <omp.h>
# if !defined(_OPENMP)
# error Undefined OpenMP version.
# endif
# include <algorithm>
# include <cstdlib>
# include <limits>
# include <string>
/* MSVC still supports omp 2.0 only */
# if defined(_MSC_VER) && !defined(__INTEL_COMPILER)
# define collapse(x)
# endif // defined(_MSC_VER) && !defined(__INTEL_COMPILER)
inline int parallel_get_max_threads() {
return omp_get_max_threads();
}
inline int parallel_get_num_threads() {
return omp_get_num_threads();
}
inline int parallel_get_thread_num() {
return omp_get_thread_num();
}
inline void parallel_set_num_threads(int n) {
omp_set_num_threads(n);
}
inline int parallel_get_env_threads() {
int env_cores = 0;
if (getenv("OMP_NUM_THREADS") != nullptr) {
try {
env_cores = std::stoi(getenv("OMP_NUM_THREADS"));
} catch (const std::exception&) {
env_cores = 0;
}
}
return env_cores;
}
inline int parallel_get_nested() {
# if _OPENMP < 201811
return omp_get_nested(); // This routine has been deprecated in OMP_5.0
# else
return omp_get_max_active_levels();
# endif
}
inline void parallel_set_nested(int enable) {
# if _OPENMP < 201811
omp_set_nested(enable); // This routine has been deprecated in OMP_5.0
# else
if (enable == 0 || omp_get_max_active_levels() == 0) {
omp_set_max_active_levels(enable);
}
# endif
}
inline int parallel_get_max_nested_levels() {
# if _OPENMP >= 200805
return omp_get_max_active_levels();
# else
return omp_get_nested() ? std::numeric_limits<int32_t>::max() : 0;
# endif
}
// Controls the number of nested parallel blocks.
// This flag has higher priority than pragma num_threads.
inline void parallel_set_max_nested_levels(int levels) {
# if _OPENMP >= 200805
omp_set_max_active_levels(levels);
# endif
}
inline int parallel_get_nested_level() {
# if _OPENMP >= 200805
return omp_get_level();
# else
return 0;
# endif
}
#elif OV_THREAD == OV_THREAD_SEQ
# include <algorithm>
inline int parallel_get_env_threads() {
return 1;
}
inline int parallel_get_max_threads() {
return 1;
}
inline int parallel_get_num_threads() {
return 1;
}
inline int parallel_get_thread_num() {
return 0;
}
inline void parallel_set_num_threads(int) {
return;
}
#endif
class ParallelNestingContext {
public:
ParallelNestingContext() {
#if OV_THREAD == OV_THREAD_OMP
# if _OPENMP >= 200805
m_origin_levels = parallel_get_max_nested_levels();
if (m_origin_levels < MAX_LEVEL) {
parallel_set_max_nested_levels(MAX_LEVEL);
}
# endif
# if _OPENMP < 201811
m_origin_nested = parallel_get_nested();
if (m_origin_nested == 0) {
parallel_set_nested(1);
}
# endif
#endif
}
~ParallelNestingContext() {
#if OV_THREAD == OV_THREAD_OMP
# if _OPENMP >= 200805
if (m_origin_levels != parallel_get_max_nested_levels()) {
parallel_set_max_nested_levels(m_origin_levels);
}
# endif
# if _OPENMP < 201811
if (m_origin_nested == 0) {
parallel_set_nested(m_origin_nested);
}
# endif
#endif
}
ParallelNestingContext(const ParallelNestingContext&) = delete;
ParallelNestingContext& operator=(const ParallelNestingContext&) = delete;
private:
#if OV_THREAD == OV_THREAD_OMP
static constexpr int MAX_LEVEL = std::numeric_limits<int>::max();
int m_origin_levels{MAX_LEVEL};
int m_origin_nested{MAX_LEVEL};
#endif
};
namespace ov {
template <typename F>
void parallel_nt(int nthr, const F& func) {
#if (OV_THREAD == OV_THREAD_TBB || OV_THREAD == OV_THREAD_TBB_AUTO)
if (nthr == 0)
nthr = parallel_get_max_threads();
if (nthr == 1) {
func(0, 1);
return;
}
tbb::parallel_for(0, nthr, [&](int ithr) {
func(ithr, nthr);
});
#elif OV_THREAD == OV_THREAD_OMP
if (nthr == 0)
nthr = parallel_get_max_threads();
if (nthr == 1) {
func(0, 1);
return;
}
// We expect the number of threads here to be "nthr", so we need to disable dynamic behavior.
auto origin_dyn_val = omp_get_dynamic();
if (origin_dyn_val != 0) {
omp_set_dynamic(0);
}
# pragma omp parallel num_threads(nthr)
{ func(parallel_get_thread_num(), parallel_get_num_threads()); }
if (origin_dyn_val != 0) {
omp_set_dynamic(origin_dyn_val);
}
#elif OV_THREAD == OV_THREAD_SEQ
func(0, 1);
#endif
}
template <typename F>
void parallel_nt_static(int nthr, const F& func) {
#if OV_THREAD == OV_THREAD_SEQ
const bool serial = true;
#else
const bool serial = false;
#endif
if (serial || nthr == 1) {
func(0, 1);
return;
}
if (nthr == 0)
nthr = parallel_get_max_threads();
#if (OV_THREAD == OV_THREAD_TBB || OV_THREAD == OV_THREAD_TBB_AUTO)
tbb::parallel_for(
0,
nthr,
[&](int ithr) {
func(ithr, nthr);
},
tbb::static_partitioner{});
#elif OV_THREAD == OV_THREAD_OMP
// We expect the number of threads here to be "nthr", so we need to disable dynamic behavior.
auto origin_dyn_val = omp_get_dynamic();
if (origin_dyn_val != 0) {
omp_set_dynamic(0);
}
# pragma omp parallel num_threads(nthr)
{ func(parallel_get_thread_num(), parallel_get_num_threads()); }
if (origin_dyn_val != 0) {
omp_set_dynamic(origin_dyn_val);
}
#endif
}
template <typename I, typename F>
void parallel_sort(I begin, I end, const F& comparator) {
#if (OV_THREAD == OV_THREAD_TBB || OV_THREAD == OV_THREAD_TBB_AUTO)
tbb::parallel_sort(begin, end, comparator);
#elif OV_THREAD == OV_THREAD_OMP
// TODO: propose OpenMP version
std::sort(begin, end, comparator);
#elif OV_THREAD == OV_THREAD_SEQ
std::sort(begin, end, comparator);
#endif
}
template <typename T0, typename R, typename F>
R parallel_sum(const T0& D0, const R& input, const F& func) {
#if (OV_THREAD == OV_THREAD_TBB || OV_THREAD == OV_THREAD_TBB_AUTO)
return _TBB_REDUCE_FUNC(
tbb::blocked_range<T0>(0, D0),
input,
[&](const tbb::blocked_range<T0>& r, R init) -> R {
R sum = init;
for (T0 dim1 = r.begin(); dim1 < r.end(); ++dim1)
sum += func(dim1);
return sum;
},
[](R x, R y) -> R {
return x + y;
} PARTITIONING);
#else
R sum = input;
# ifdef _MSC_VER
using T0_IT = typename std::make_signed<T0>::type;
# else
using T0_IT = T0;
# endif
# if OV_THREAD == OV_THREAD_OMP
# pragma omp parallel for reduction(+ : sum) schedule(static)
# endif
for (T0_IT dim1 = 0; dim1 < static_cast<T0_IT>(D0); dim1++) {
sum += static_cast<R>(func(dim1));
}
return sum;
#endif
}
template <typename T0, typename T1, typename R, typename F>
R parallel_sum2d(const T0& D0, const T1& D1, const R& input, const F& func) {
#if (OV_THREAD == OV_THREAD_TBB || OV_THREAD == OV_THREAD_TBB_AUTO)
return _TBB_REDUCE_FUNC(
tbb::blocked_range2d<T0, T1>(0, D0, 0, D1),
input,
[&](const tbb::blocked_range2d<T0, T1>& r, R init) -> R {
R sum = init;
for (T0 dim2 = r.rows().begin(); dim2 < r.rows().end(); dim2++) {
for (T1 dim1 = r.cols().begin(); dim1 < r.cols().end(); dim1++) {
sum += func(dim2, dim1);
}
}
return sum;
},
[](R x, R y) -> R {
return x + y;
} PARTITIONING);
#else
R sum = input;
# ifdef _MSC_VER
using T0_IT = typename std::make_signed<T0>::type;
using T1_IT = typename std::make_signed<T1>::type;
# else
using T0_IT = T0;
using T1_IT = T1;
# endif
# if OV_THREAD == OV_THREAD_OMP
# pragma omp parallel for collapse(2) reduction(+ : sum) schedule(static)
# endif
for (T0_IT dim2 = 0; dim2 < D0; dim2++) {
for (T1_IT dim1 = 0; dim1 < D1; dim1++) {
sum += func(dim2, dim1);
}
}
return sum;
#endif
}
template <typename T0, typename T1, typename T2, typename R, typename F>
R parallel_sum3d(const T0& D0, const T1& D1, const T2& D2, const R& input, const F& func) {
#if (OV_THREAD == OV_THREAD_TBB || OV_THREAD == OV_THREAD_TBB_AUTO)
return _TBB_REDUCE_FUNC(
tbb::blocked_range3d<T0, T1, T2>(0, D0, 0, D1, 0, D2),
input,
[&](const tbb::blocked_range3d<T0, T1, T2>& r, R init) -> R {
R sum = init;
for (T0 dim1 = r.pages().begin(); dim1 < r.pages().end(); dim1++) {
for (T1 dim2 = r.rows().begin(); dim2 < r.rows().end(); dim2++) {
for (T2 dim3 = r.cols().begin(); dim3 < r.cols().end(); dim3++) {
sum += func(dim1, dim2, dim3);
}
}
}
return sum;
},
[](R x, R y) -> R {
return x + y;
} PARTITIONING);
#else
R sum = input;
# ifdef _MSC_VER
using T0_IT = typename std::make_signed<T0>::type;
using T1_IT = typename std::make_signed<T1>::type;
using T2_IT = typename std::make_signed<T2>::type;
# else
using T0_IT = T0;
using T1_IT = T1;
using T2_IT = T2;
# endif
# if OV_THREAD == OV_THREAD_OMP
# pragma omp parallel for collapse(3) reduction(+ : sum) schedule(static)
# endif
for (T0_IT dim1 = 0; dim1 < static_cast<T0_IT>(D0); dim1++) {
for (T1_IT dim2 = 0; dim2 < static_cast<T1_IT>(D1); dim2++) {
for (T2_IT dim3 = 0; dim3 < static_cast<T2_IT>(D2); dim3++) {
sum += func(dim1, dim2, dim3);
}
}
}
return sum;
#endif
}
template <typename T>
inline T parallel_it_init(T start) {
return start;
}
template <typename T, typename Q, typename R, typename... Args>
inline T parallel_it_init(T start, Q& x, const R& X, Args&&... tuple) {
start = parallel_it_init(start, static_cast<Args>(tuple)...);
x = start % X;
return start / X;
}
inline bool parallel_it_step() {
return true;
}
template <typename Q, typename R, typename... Args>
inline bool parallel_it_step(Q& x, const R& X, Args&&... tuple) {
if (parallel_it_step(static_cast<Args>(tuple)...)) {
if (++x - X == 0) {
x = 0;
return true;
}
}
return false;
}
template <typename T, typename Q>
inline void splitter(const T& n, const Q& team, const Q& tid, T& n_start, T& n_end) {
if (team <= 1 || n == 0) {
n_start = 0;
n_end = n;
} else {
T n1 = (n + (T)team - 1) / (T)team;
T n2 = n1 - 1;
T T1 = n - n2 * (T)team;
n_end = (T)tid < T1 ? n1 : n2;
n_start = (T)tid <= T1 ? tid * n1 : T1 * n1 + ((T)tid - T1) * n2;
}
n_end += n_start;
}
namespace helpers {
template <typename T>
struct NumOfLambdaArgs : public NumOfLambdaArgs<decltype(&T::operator())> {};
template <typename C, typename R, typename... Args>
struct NumOfLambdaArgs<R (C::*)(Args...) const> {
constexpr static int value = sizeof...(Args);
};
template <typename ACT, typename... T, size_t N_ARGS = NumOfLambdaArgs<ACT>::value>
typename std::enable_if<N_ARGS == sizeof...(T) + 2, void>::type call_with_args(const ACT& body,
size_t g_id,
size_t iwork,
T... arg) {
body(g_id, iwork, arg...);
}
template <typename ACT, typename... T, size_t N_ARGS = NumOfLambdaArgs<ACT>::value>
typename std::enable_if<N_ARGS == sizeof...(T) + 1, void>::type call_with_args(const ACT& body,
size_t g_id,
size_t iwork,
T... arg) {
body(g_id, arg...);
}
template <typename ACT, typename... T, size_t N_ARGS = NumOfLambdaArgs<ACT>::value>
typename std::enable_if<N_ARGS == sizeof...(T), void>::type call_with_args(const ACT& body,
size_t g_id,
size_t iwork,
T... arg) {
body(arg...);
}
} // namespace helpers
template <typename T0, typename F>
void for_1d(const int& ithr, const int& nthr, const T0& D0, const F& func) {
T0 d0{0}, end{0};
splitter(D0, nthr, ithr, d0, end);
for (; d0 < end; ++d0)
helpers::call_with_args(func, ithr, d0, d0);
}
template <typename T0, typename F>
void parallel_for(const T0& D0, const F& func) {
if (D0 == T0(0)) {
return;
}
#if OV_THREAD == OV_THREAD_TBB
auto work_amount = static_cast<size_t>(D0);
int nthr = parallel_get_max_threads();
if (static_cast<size_t>(nthr) > work_amount)
nthr = static_cast<int>(work_amount);
if (nthr == 1) {
for_1d(0, 1, D0, func);
} else {
tbb::parallel_for(
0,
nthr,
[&](int ithr) {
for_1d(ithr, nthr, D0, func);
},
tbb::static_partitioner());
}
#elif OV_THREAD == OV_THREAD_TBB_AUTO
const int nthr = parallel_get_max_threads();
tbb::parallel_for(0, nthr, [&](int ithr) {
for_1d(ithr, nthr, D0, func);
});
#elif OV_THREAD == OV_THREAD_OMP
// Please note that this function does not guarantee execution on the same number of threads from call to call.
// Use the parallel_nt* functions if the procedure depends on a certain number of threads.
auto work_amount = static_cast<size_t>(D0);
auto nthr = omp_get_max_threads();
if (parallel_get_nested_level() > 0) {
nthr /= omp_get_num_threads();
}
if (static_cast<size_t>(nthr) > work_amount) {
nthr = static_cast<int>(work_amount);
}
if (nthr == 1) {
for_1d(0, 1, D0, func);
} else {
# pragma omp parallel
{ for_1d(parallel_get_thread_num(), parallel_get_num_threads(), D0, func); }
}
#elif OV_THREAD == OV_THREAD_SEQ
for_1d(0, 1, D0, func);
#endif
}
template <typename T0, typename T1, typename F>
void for_2d(const int& ithr, const int& nthr, const T0& D0, const T1& D1, const F& func) {
const size_t work_amount = (size_t)D0 * D1;
if (work_amount == 0)
return;
size_t start{0}, end{0};
splitter(work_amount, nthr, ithr, start, end);
T0 d0{0};
T1 d1{0};
parallel_it_init(start, d0, D0, d1, D1);
for (size_t iwork = start; iwork < end; ++iwork) {
helpers::call_with_args(func, ithr, iwork, d0, d1);
parallel_it_step(d0, D0, d1, D1);
}
}
template <typename T0, typename T1, typename F>
void parallel_for2d(const T0& D0, const T1& D1, const F& func) {
if (D0 == T0(0) || D1 == T1(0)) {
return;
}
#if OV_THREAD == OV_THREAD_TBB
auto work_amount = static_cast<size_t>(D0 * D1);
int nthr = parallel_get_max_threads();
if (static_cast<size_t>(nthr) > work_amount)
nthr = static_cast<int>(work_amount);
if (nthr == 1) {
for_2d(0, 1, D0, D1, func);
} else {
tbb::parallel_for(
0,
nthr,
[&](int ithr) {
for_2d(ithr, nthr, D0, D1, func);
},
tbb::static_partitioner());
}
#elif OV_THREAD == OV_THREAD_TBB_AUTO
const int nthr = parallel_get_max_threads();
tbb::parallel_for(0, nthr, [&](int ithr) {
for_2d(ithr, nthr, D0, D1, func);
});
#elif OV_THREAD == OV_THREAD_OMP
// Please note that this function does not guarantee execution on the same number of threads from call to call.
// Use the parallel_nt* functions if the procedure depends on a certain number of threads.
auto work_amount = static_cast<int>(D0 * D1);
auto nthr = omp_get_max_threads();
if (parallel_get_nested_level() > 0) {
nthr /= omp_get_num_threads();
}
if (nthr > work_amount) {
nthr = work_amount;
}
if (nthr == 1) {
for_2d(0, 1, D0, D1, func);
} else {
# pragma omp parallel
{ for_2d(parallel_get_thread_num(), parallel_get_num_threads(), D0, D1, func); }
}
#elif OV_THREAD == OV_THREAD_SEQ
for_2d(0, 1, D0, D1, func);
#endif
}
template <typename T0, typename T1, typename F>
void parallel_for2d_dynamic(const T0& D0, const T1& D1, const F& func) {
#if (OV_THREAD == OV_THREAD_TBB || OV_THREAD == OV_THREAD_TBB_AUTO)
tbb::parallel_for(tbb::blocked_range2d<T0, T1>(0, D0, 0, D1), [=](const tbb::blocked_range2d<T0, T1>& r) {
for (T0 d0 = r.rows().begin(); d0 < r.rows().end(); d0++) {
for (T1 d1 = r.cols().begin(); d1 < r.cols().end(); d1++) {
func(d0, d1);
}
}
});
#else
parallel_for2d(D0, D1, [&](size_t d0, size_t d1) {
func(d0, d1);
});
#endif
}
template <typename T0, typename T1, typename T2, typename F>
void for_3d(const int& ithr, const int& nthr, const T0& D0, const T1& D1, const T2& D2, const F& func) {
const size_t work_amount = (size_t)D0 * D1 * D2;
if (work_amount == 0)
return;
size_t start{0}, end{0};
splitter(work_amount, nthr, ithr, start, end);
T0 d0{0};
T1 d1{0};
T2 d2{0};
parallel_it_init(start, d0, D0, d1, D1, d2, D2);
for (size_t iwork = start; iwork < end; ++iwork) {
helpers::call_with_args(func, ithr, iwork, d0, d1, d2);
parallel_it_step(d0, D0, d1, D1, d2, D2);
}
}
template <typename T0, typename T1, typename T2, typename F>
void parallel_for3d(const T0& D0, const T1& D1, const T2& D2, const F& func) {
if (D0 == T0(0) || D1 == T1(0) || D2 == T2(0)) {
return;
}
#if OV_THREAD == OV_THREAD_TBB
auto work_amount = static_cast<size_t>(D0 * D1 * D2);
int nthr = parallel_get_max_threads();
if (static_cast<size_t>(nthr) > work_amount)
nthr = static_cast<int>(work_amount);
if (nthr == 1) {
for_3d(0, 1, D0, D1, D2, func);
} else {
tbb::parallel_for(
0,
nthr,
[&](int ithr) {
for_3d(ithr, nthr, D0, D1, D2, func);
},
tbb::static_partitioner());
}
#elif OV_THREAD == OV_THREAD_TBB_AUTO
const int nthr = parallel_get_max_threads();
tbb::parallel_for(0, nthr, [&](int ithr) {
for_3d(ithr, nthr, D0, D1, D2, func);
});
#elif OV_THREAD == OV_THREAD_OMP
// Please note that this function does not guarantee execution on the same number of threads from call to call.
// Use the parallel_nt* functions if the procedure depends on a certain number of threads.
auto work_amount = static_cast<int>(D0 * D1 * D2);
auto nthr = parallel_get_max_threads();
if (parallel_get_nested_level() > 0) {
nthr /= omp_get_num_threads();
}
if (nthr > work_amount) {
nthr = work_amount;
}
if (nthr == 1) {
for_3d(0, 1, D0, D1, D2, func);
} else {
# pragma omp parallel
{ for_3d(parallel_get_thread_num(), parallel_get_num_threads(), D0, D1, D2, func); }
}
#elif OV_THREAD == OV_THREAD_SEQ
for_3d(0, 1, D0, D1, D2, func);
#endif
}
template <typename T0, typename T1, typename T2, typename F>
void parallel_for3d_dynamic(const T0& D0, const T1& D1, const T2& D2, const F& func) {
#if (OV_THREAD == OV_THREAD_TBB || OV_THREAD == OV_THREAD_TBB_AUTO)
tbb::parallel_for(tbb::blocked_range3d<T0, T1, T2>(0, D0, 0, D1, 0, D2),
[=](const tbb::blocked_range3d<T0, T1, T2>& r) {
for (T0 d0 = r.pages().begin(); d0 < r.pages().end(); d0++) {
for (T1 d1 = r.rows().begin(); d1 < r.rows().end(); d1++) {
for (T2 d2 = r.cols().begin(); d2 < r.cols().end(); d2++) {
func(d0, d1, d2);
}
}
}
});
#else
parallel_for3d(D0, D1, D2, [&](size_t d0, size_t d1, size_t d2) {
func(d0, d1, d2);
});
#endif
}
template <typename T0, typename T1, typename T2, typename T3, typename F>
void for_4d(const int& ithr, const int& nthr, const T0& D0, const T1& D1, const T2& D2, const T3& D3, const F& func) {
const size_t work_amount = (size_t)D0 * D1 * D2 * D3;
if (work_amount == 0)
return;
size_t start{0}, end{0};
splitter(work_amount, nthr, ithr, start, end);
T0 d0{0};
T1 d1{0};
T2 d2{0};
T3 d3{0};
parallel_it_init(start, d0, D0, d1, D1, d2, D2, d3, D3);
for (size_t iwork = start; iwork < end; ++iwork) {
helpers::call_with_args(func, ithr, iwork, d0, d1, d2, d3);
parallel_it_step(d0, D0, d1, D1, d2, D2, d3, D3);
}
}
template <typename T0, typename T1, typename T2, typename T3, typename F>
void parallel_for4d(const T0& D0, const T1& D1, const T2& D2, const T3& D3, const F& func) {
if (D0 == T0(0) || D1 == T1(0) || D2 == T2(0) || D3 == T3(0)) {
return;
}
#if OV_THREAD == OV_THREAD_TBB
auto work_amount = static_cast<size_t>(D0 * D1 * D2 * D3);
int nthr = parallel_get_max_threads();
if (static_cast<size_t>(nthr) > work_amount)
nthr = static_cast<int>(work_amount);
if (nthr == 1) {
for_4d(0, 1, D0, D1, D2, D3, func);
} else {
tbb::parallel_for(
0,
nthr,
[&](int ithr) {
for_4d(ithr, nthr, D0, D1, D2, D3, func);
},
tbb::static_partitioner());
}
#elif OV_THREAD == OV_THREAD_TBB_AUTO
const int nthr = parallel_get_max_threads();
tbb::parallel_for(0, nthr, [&](int ithr) {
for_4d(ithr, nthr, D0, D1, D2, D3, func);
});
#elif OV_THREAD == OV_THREAD_OMP
// Please note that this function does not guarantee execution on the same number of threads from call to call.
// Use the parallel_nt* functions if the procedure depends on a certain number of threads.
auto work_amount = static_cast<int>(D0 * D1 * D2 * D3);
auto nthr = parallel_get_max_threads();
if (parallel_get_nested_level() > 0) {
nthr /= omp_get_num_threads();
}
if (nthr > work_amount) {
nthr = work_amount;
}
if (nthr == 1) {
for_4d(0, 1, D0, D1, D2, D3, func);
} else {
# pragma omp parallel
{ for_4d(parallel_get_thread_num(), parallel_get_num_threads(), D0, D1, D2, D3, func); }
}
#elif OV_THREAD == OV_THREAD_SEQ
for_4d(0, 1, D0, D1, D2, D3, func);
#endif
}
template <typename T0, typename T1, typename T2, typename T3, typename T4, typename F>
void for_5d(const int& ithr,
const int& nthr,
const T0& D0,
const T1& D1,
const T2& D2,
const T3& D3,
const T4& D4,
const F& func) {
const size_t work_amount = (size_t)D0 * D1 * D2 * D3 * D4;
if (work_amount == 0)
return;
size_t start{0}, end{0};
splitter(work_amount, nthr, ithr, start, end);
T0 d0{0};
T1 d1{0};
T2 d2{0};
T3 d3{0};
T4 d4{0};
parallel_it_init(start, d0, D0, d1, D1, d2, D2, d3, D3, d4, D4);
for (size_t iwork = start; iwork < end; ++iwork) {
helpers::call_with_args(func, ithr, iwork, d0, d1, d2, d3, d4);
parallel_it_step(d0, D0, d1, D1, d2, D2, d3, D3, d4, D4);
}
}
template <typename T0, typename T1, typename T2, typename T3, typename T4, typename F>
void parallel_for5d(const T0& D0, const T1& D1, const T2& D2, const T3& D3, const T4& D4, const F& func) {
if (D0 == T0(0) || D1 == T1(0) || D2 == T2(0) || D3 == T3(0) || D4 == T4(0)) {
return;
}
#if OV_THREAD == OV_THREAD_TBB
auto work_amount = static_cast<size_t>(D0 * D1 * D2 * D3 * D4);
int nthr = parallel_get_max_threads();
if (static_cast<size_t>(nthr) > work_amount)
nthr = static_cast<int>(work_amount);
if (nthr == 1) {
for_5d(0, 1, D0, D1, D2, D3, D4, func);
} else {
tbb::parallel_for(
0,
nthr,
[&](int ithr) {
for_5d(ithr, nthr, D0, D1, D2, D3, D4, func);
},
tbb::static_partitioner());
}
#elif OV_THREAD == OV_THREAD_TBB_AUTO
const int nthr = parallel_get_max_threads();
tbb::parallel_for(0, nthr, [&](int ithr) {
for_5d(ithr, nthr, D0, D1, D2, D3, D4, func);
});
#elif OV_THREAD == OV_THREAD_OMP
// Please note that this function does not guarantee execution on the same number of threads from call to call.
// Use the parallel_nt* functions if the procedure depends on a certain number of threads.
auto work_amount = static_cast<int>(D0 * D1 * D2 * D3 * D4);
auto nthr = parallel_get_max_threads();
if (parallel_get_nested_level() > 0) {
nthr /= omp_get_num_threads();
}
if (nthr > work_amount) {
nthr = work_amount;
}
if (nthr == 1) {
for_5d(0, 1, D0, D1, D2, D3, D4, func);
} else {
# pragma omp parallel
{ for_5d(parallel_get_thread_num(), parallel_get_num_threads(), D0, D1, D2, D3, D4, func); }
}
#elif OV_THREAD == OV_THREAD_SEQ
for_5d(0, 1, D0, D1, D2, D3, D4, func);
#endif
}
template <typename T0, typename T1, typename T2, typename T3, typename T4, typename T5, typename F>
void for_6d(const int& ithr,
const int& nthr,
const T0& D0,
const T1& D1,
const T2& D2,
const T3& D3,
const T4& D4,
const T5& D5,
const F& func) {
const size_t work_amount = (size_t)D0 * D1 * D2 * D3 * D4 * D5;
if (work_amount == 0)
return;
size_t start{0}, end{0};
splitter(work_amount, nthr, ithr, start, end);
T0 d0{0};
T1 d1{0};
T2 d2{0};
T3 d3{0};
T4 d4{0};
T5 d5{0};
parallel_it_init(start, d0, D0, d1, D1, d2, D2, d3, D3, d4, D4, d5, D5);
for (size_t iwork = start; iwork < end; ++iwork) {
helpers::call_with_args(func, ithr, iwork, d0, d1, d2, d3, d4, d5);
parallel_it_step(d0, D0, d1, D1, d2, D2, d3, D3, d4, D4, d5, D5);
}
}
template <typename T0, typename T1, typename T2, typename T3, typename T4, typename T5, typename F>
void parallel_for6d(const T0& D0, const T1& D1, const T2& D2, const T3& D3, const T4& D4, const T5& D5, const F& func) {
if (D0 == T0(0) || D1 == T1(0) || D2 == T2(0) || D3 == T3(0) || D4 == T4(0) || D5 == T5(0)) {
return;
}
#if OV_THREAD == OV_THREAD_TBB
auto work_amount = static_cast<size_t>(D0 * D1 * D2 * D3 * D4 * D5);
int nthr = parallel_get_max_threads();
if (static_cast<size_t>(nthr) > work_amount)
nthr = static_cast<int>(work_amount);
if (nthr == 1) {
for_6d(0, 1, D0, D1, D2, D3, D4, D5, func);
} else {
tbb::parallel_for(
0,
nthr,
[&](int ithr) {
for_6d(ithr, nthr, D0, D1, D2, D3, D4, D5, func);
},
tbb::static_partitioner());
}
#elif OV_THREAD == OV_THREAD_TBB_AUTO
const int nthr = parallel_get_max_threads();
tbb::parallel_for(0, nthr, [&](int ithr) {
for_6d(ithr, nthr, D0, D1, D2, D3, D4, D5, func);
});
#elif OV_THREAD == OV_THREAD_OMP
// Please note that this function does not guarantee execution on the same number of threads from call to call.
// Use the parallel_nt* functions if the procedure depends on a certain number of threads.
auto work_amount = static_cast<int>(D0 * D1 * D2 * D3 * D4 * D5);
auto nthr = parallel_get_max_threads();
if (parallel_get_nested_level() > 0) {
nthr /= omp_get_num_threads();
}
if (nthr > work_amount) {
nthr = work_amount;
}
if (nthr == 1) {
for_6d(0, 1, D0, D1, D2, D3, D4, D5, func);
} else {
# pragma omp parallel
{ for_6d(parallel_get_thread_num(), parallel_get_num_threads(), D0, D1, D2, D3, D4, D5, func); }
}
#elif OV_THREAD == OV_THREAD_SEQ
for_6d(0, 1, D0, D1, D2, D3, D4, D5, func);
#endif
}
} // namespace ov
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