cpp-taskflow/taskflow/algorithm/reduce.hpp at master · aimoonchen/cpp-taskflow · GitHub

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#pragma once

#include "../taskflow.hpp"

namespace tf {

// Function: make_reduce_task

template <typename B, typename E, typename T, typename O, typename P = DefaultPartitioner>

auto make_reduce_task(B b, E e, T& init, O bop, P part = P()) {

using namespace std::string_literals;

using B_t = std::decay_t<unwrap_ref_decay_t<B>>;

using E_t = std::decay_t<unwrap_ref_decay_t<E>>;

return [=, &r=init] (Runtime& rt) mutable {

// fetch the iterator values

B_t beg = b;

E_t end = e;

size_t W = rt.executor().num_workers();

size_t N = std::distance(beg, end);

// only myself - no need to spawn another graph

if(W <= 1 || N <= part.chunk_size()) {

part([&](){ for(; beg!=end; r = bop(r, *beg++)); })();

return;

}

PreemptionGuard preemption_guard(rt);

if(N < W) {

W = N;

}

auto mutex = std::make_shared<std::mutex>();

// static partitioner

if constexpr(part.type() == PartitionerType::STATIC) {

for(size_t w=0, curr_b=0; w<W && curr_b < N;) {

// we force chunk size to be at least two because the temporary

// variable sum need to avoid copy at the first step

auto chunk_size = std::max(size_t{2}, part.adjusted_chunk_size(N, W, w));

auto task = part([=, &r] () mutable {

std::advance(beg, curr_b);

if(N - curr_b == 1) {

std::lock_guard<std::mutex> lock(*mutex);

r = bop(r, *beg);

return;

}

auto beg1 = beg++;

auto beg2 = beg++;

T sum = bop(*beg1, *beg2);

// loop reduce

part.loop(N, W, curr_b, chunk_size,

[=, &sum, prev_e=curr_b+2](size_t part_b, size_t part_e) mutable {

if(part_b > prev_e) {

std::advance(beg, part_b - prev_e);

}

else {

part_b = prev_e;

}

for(size_t x=part_b; x<part_e; x++, beg++) {

sum = bop(sum, *beg);

}

prev_e = part_e;

}

);

// final reduce

std::lock_guard<std::mutex> lock(*mutex);

r = bop(r, sum);

});

(++w == W || (curr_b += chunk_size) >= N) ? task() : rt.silent_async(task);

}

// dynamic partitioner

else {

auto next = std::make_shared<std::atomic<size_t>>(0);

for(size_t w=0; w<W;) {

auto task = part([=, &r] () mutable {

// pre-reduce

size_t s0 = next->fetch_add(2, std::memory_order_relaxed);

if(s0 >= N) {

return;

}

std::advance(beg, s0);

if(N - s0 == 1) {

std::lock_guard<std::mutex> lock(*mutex);

r = bop(r, *beg);

return;

}

auto beg1 = beg++;

auto beg2 = beg++;

T sum = bop(*beg1, *beg2);

// loop reduce

part.loop(N, W, *next,

[=, &sum, prev_e=s0+2](size_t curr_b, size_t curr_e) mutable {

std::advance(beg, curr_b - prev_e);

for(size_t x=curr_b; x<curr_e; x++, beg++) {

sum = bop(sum, *beg);

}

prev_e = curr_e;

}

);

// final reduce

std::lock_guard<std::mutex> lock(*mutex);

r = bop(r, sum);

});

(++w == W) ? task() : rt.silent_async(task);

}

};

}

// Function: make_transform_reduce_task

template <

typename B, typename E, typename T, typename BOP, typename UOP,

typename P = DefaultPartitioner

auto make_transform_reduce_task(B b, E e, T& init, BOP bop, UOP uop, P part = P()) {

using namespace std::string_literals;

using B_t = std::decay_t<unwrap_ref_decay_t<B>>;

using E_t = std::decay_t<unwrap_ref_decay_t<E>>;

return [=, &r=init] (Runtime& rt) mutable {

// fetch the iterator values

B_t beg = b;

E_t end = e;

size_t W = rt.executor().num_workers();

size_t N = std::distance(beg, end);

// only myself - no need to spawn another graph

if(W <= 1 || N <= part.chunk_size()) {

part([&](){ for(; beg!=end; r = bop(std::move(r), uop(*beg++))); })();

return;

}

PreemptionGuard preemption_guard(rt);

if(N < W) {

W = N;

}

auto mutex = std::make_shared<std::mutex>();

// static partitioner

if constexpr(part.type() == PartitionerType::STATIC) {

for(size_t w=0, curr_b=0; w<W && curr_b < N;) {

auto chunk_size = part.adjusted_chunk_size(N, W, w);

auto task = part([=, &r] () mutable {

std::advance(beg, curr_b);

if(N - curr_b == 1) {

std::lock_guard<std::mutex> lock(*mutex);

r = bop(std::move(r), uop(*beg));

return;

}

//auto beg1 = beg++;

//auto beg2 = beg++;

//T sum = bop(uop(*beg1), uop(*beg2));

T sum = (chunk_size == 1) ? uop(*beg++) : bop(uop(*beg++), uop(*beg++));

// loop reduce

part.loop(N, W, curr_b, chunk_size,

[=, &sum, prev_e=curr_b+(chunk_size == 1 ? 1 : 2)]

(size_t part_b, size_t part_e) mutable {

if(part_b > prev_e) {

std::advance(beg, part_b - prev_e);

}

else {

part_b = prev_e;

}

for(size_t x=part_b; x<part_e; x++, beg++) {

sum = bop(std::move(sum), uop(*beg));

}

prev_e = part_e;

}

);

// final reduce

std::lock_guard<std::mutex> lock(*mutex);

r = bop(std::move(r), std::move(sum));

});

(++w == W || (curr_b += chunk_size) >= N) ? task() : rt.silent_async(task);

}

// dynamic partitioner

else {

auto next = std::make_shared<std::atomic<size_t>>(0);

for(size_t w=0; w<W;) {

auto task = part([=, &r] () mutable {

// pre-reduce

size_t s0 = next->fetch_add(2, std::memory_order_relaxed);

if(s0 >= N) {

return;

}

std::advance(beg, s0);

if(N - s0 == 1) {

std::lock_guard<std::mutex> lock(*mutex);

r = bop(std::move(r), uop(*beg));

return;

}

auto beg1 = beg++;

auto beg2 = beg++;

T sum = bop(uop(*beg1), uop(*beg2));

// loop reduce

part.loop(N, W, *next,

[=, &sum, prev_e=s0+2](size_t curr_b, size_t curr_e) mutable {

std::advance(beg, curr_b - prev_e);

for(size_t x=curr_b; x<curr_e; x++, beg++) {

sum = bop(std::move(sum), uop(*beg));

}

prev_e = curr_e;

}

);

// final reduce

std::lock_guard<std::mutex> lock(*mutex);

r = bop(std::move(r), std::move(sum));

});

(++w == W) ? task() : rt.silent_async(task);

}

};

}

// Function: make_transform_reduce_task with two binary operation

template <

typename B1, typename E1, typename B2, typename T, typename BOP_R, typename BOP_T,

typename P = DefaultPartitioner,

std::enable_if_t<!is_partitioner_v<std::decay_t<BOP_T>>, void>* = nullptr

auto make_transform_reduce_task(

B1 b1, E1 e1, B2 b2, T& init, BOP_R bop_r, BOP_T bop_t, P part = P()

) {

using namespace std::string_literals;

using B1_t = std::decay_t<unwrap_ref_decay_t<B1>>;

using E1_t = std::decay_t<unwrap_ref_decay_t<E1>>;

using B2_t = std::decay_t<unwrap_ref_decay_t<B2>>;

return [=, &r=init] (Runtime& rt) mutable {

// fetch the iterator values

B1_t beg1 = b1;

E1_t end1 = e1;

B2_t beg2 = b2;

size_t W = rt.executor().num_workers();

size_t N = std::distance(beg1, end1);

// only myself - no need to spawn another graph

if(W <= 1 || N <= part.chunk_size()) {

part([&](){ for(; beg1!=end1; r = bop_r(std::move(r), bop_t(*beg1++, *beg2++))); })();

return;

}

PreemptionGuard preemption_guard(rt);

if(N < W) {

W = N;

}

auto mutex = std::make_shared<std::mutex>();

// static partitioner

if constexpr(part.type() == PartitionerType::STATIC) {

for(size_t w=0, curr_b=0; w<W && curr_b < N;) {

auto chunk_size = part.adjusted_chunk_size(N, W, w);

auto task = part([=, &r] () mutable {

std::advance(beg1, curr_b);

std::advance(beg2, curr_b);

if(N - curr_b == 1) {

std::lock_guard<std::mutex> lock(*mutex);

r = bop_r(std::move(r), bop_t(*beg1, *beg2));

return;

}

T sum = (chunk_size == 1) ? bop_t(*beg1++, *beg2++) :

bop_r(bop_t(*beg1++, *beg2++), bop_t(*beg1++, *beg2++));

// loop reduce

part.loop(N, W, curr_b, chunk_size,

[=, &sum, prev_e=curr_b+(chunk_size == 1 ? 1 : 2)]

(size_t part_b, size_t part_e) mutable {

if(part_b > prev_e) {

std::advance(beg1, part_b - prev_e);

std::advance(beg2, part_b - prev_e);

}

else {

part_b = prev_e;

}

for(size_t x=part_b; x<part_e; x++, beg1++, beg2++) {

sum = bop_r(std::move(sum), bop_t(*beg1, *beg2));

}

prev_e = part_e;

}

);

// final reduce

std::lock_guard<std::mutex> lock(*mutex);

r = bop_r(std::move(r), std::move(sum));

});

(++w == W || (curr_b += chunk_size) >= N) ? task() : rt.silent_async(task);

}

// dynamic partitioner

else {

auto next = std::make_shared<std::atomic<size_t>>(0);

for(size_t w=0; w<W;) {

auto task = part([=, &r] () mutable {

// pre-reduce

size_t s0 = next->fetch_add(2, std::memory_order_relaxed);

if(s0 >= N) {

return;

}

std::advance(beg1, s0);

std::advance(beg2, s0);

if(N - s0 == 1) {

std::lock_guard<std::mutex> lock(*mutex);

r = bop_r(std::move(r), bop_t(*beg1, *beg2));

return;

}

auto beg11 = beg1++;

auto beg12 = beg1++;

auto beg21 = beg2++;

auto beg22 = beg2++;

T sum = bop_r(bop_t(*beg11, *beg21), bop_t(*beg12, *beg22));

// loop reduce

part.loop(N, W, *next,

[=, &sum, prev_e=s0+2](size_t curr_b, size_t curr_e) mutable {

std::advance(beg1, curr_b - prev_e);

std::advance(beg2, curr_b - prev_e);

for(size_t x=curr_b; x<curr_e; x++, beg1++, beg2++) {

sum = bop_r(std::move(sum), bop_t(*beg1, *beg2));

}

prev_e = curr_e;

}

);

// final reduce

std::lock_guard<std::mutex> lock(*mutex);

r = bop_r(std::move(r), std::move(sum));

});

(++w == W) ? task() : rt.silent_async(task);

}

};

}

// Function: make_reduce_by_index_task

template <typename R, typename T, typename L, typename G, typename P = DefaultPartitioner>

auto make_reduce_by_index_task(R range, T& init, L lop, G gop, P part = P()) {

using range_type = std::decay_t<unwrap_ref_decay_t<R>>;

return [=, &init] (Runtime& rt) mutable {

// fetch the iterator values

range_type r = range;

// nothing to be done if the range is invalid

if(is_index_range_invalid(r.begin(), r.end(), r.step_size())) {

return;

}

size_t W = rt.executor().num_workers();

size_t N = r.size();

// only myself - no need to spawn another graph

if(W <= 1 || N <= part.chunk_size()) {

part([&](){ init = lop(r, std::move(init)); })();

return;

}

PreemptionGuard preemption_guard(rt);

if(N < W) {

W = N;

}

auto mutex = std::make_shared<std::mutex>();

// static partitioner

if constexpr(part.type() == PartitionerType::STATIC) {

for(size_t w=0, curr_b=0; w<W && curr_b < N;) {

// we force chunk size to be at least two because the temporary

// variable sum need to avoid copy at the first step

auto chunk_size = part.adjusted_chunk_size(N, W, w);

auto task = part([=, &init] () mutable {

// temporary result so far

std::optional<T> tmp;

// loop reduce

part.loop(N, W, curr_b, chunk_size, [=, &tmp](size_t part_b, size_t part_e) mutable {

tmp = lop(r.discrete_domain(part_b, part_e), std::move(tmp));

});

// final reduce - tmp is guaranteed to have value

// assert(tmp.has_value());

std::lock_guard<std::mutex> lock(*mutex);

init = gop(std::move(init), std::move(*tmp));

});

(++w == W || (curr_b += chunk_size) >= N) ? task() : rt.silent_async(task);

}

// dynamic partitioner

else {

auto next = std::make_shared<std::atomic<size_t>>(0);

for(size_t w=0; w<W;) {

auto task = part([=, &init] () mutable {

// temporary result so far

std::optional<T> tmp;

// loop reduce

part.loop(N, W, *next, [=, &tmp](size_t part_b, size_t part_e) mutable {

tmp = lop(r.discrete_domain(part_b, part_e), std::move(tmp));

});

// final reduce - need to check if the running total has value since

// this is a dynamic scheduler; the worker may not actually acquire any work

if(tmp) {

std::lock_guard<std::mutex> lock(*mutex);

init = gop(std::move(init), std::move(*tmp));

}

});

(++w == W) ? task() : rt.silent_async(task);

}

};

}

// ------------------------------------------------------------------------------------------------

// default reduction

// ------------------------------------------------------------------------------------------------

// Function: reduce

template <typename B, typename E, typename T, typename O, typename P>

Task FlowBuilder::reduce(B beg, E end, T& init, O bop, P part) {

return emplace(make_reduce_task(beg, end, init, bop, part));

}

// ------------------------------------------------------------------------------------------------

// default transform and reduction

// ------------------------------------------------------------------------------------------------

// Function: transform_reduce

template <typename B, typename E, typename T, typename BOP, typename UOP, typename P,

std::enable_if_t<is_partitioner_v<std::decay_t<P>>, void>*

Task FlowBuilder::transform_reduce(

B beg, E end, T& init, BOP bop, UOP uop, P part

) {

return emplace(make_transform_reduce_task(beg, end, init, bop, uop, part));

}

// Function: transform_reduce

template <

typename B1, typename E1, typename B2, typename T, typename BOP_R, typename BOP_T,

typename P,

std::enable_if_t<!is_partitioner_v<std::decay_t<BOP_T>>, void>*

Task FlowBuilder::transform_reduce(

B1 beg1, E1 end1, B2 beg2, T& init, BOP_R bop_r, BOP_T bop_t, P part

) {

return emplace(make_transform_reduce_task(beg1, end1, beg2, init, bop_r, bop_t, part));

}

// ------------------------------------------------------------------------------------------------

// default reduce_by_key

// ------------------------------------------------------------------------------------------------

// Function: make_index_reduce_task

template <typename R, typename T, typename L, typename G, typename P>

Task FlowBuilder::reduce_by_index(R range, T& init, L lop, G gop, P part) {

return emplace(make_reduce_by_index_task(range, init, lop, gop, part));

}

} // end of namespace tf -------------------------------------------------------------------------

cpp-taskflow/taskflow/algorithm/reduce.hpp at master · aimoonchen/cpp-taskflow · GitHub

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