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/* Parallel for loops
Copyright (C) 2019-2022 Free Software Foundation, Inc.
This file is part of GDB.
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>. */
#ifndef GDBSUPPORT_PARALLEL_FOR_H
#define GDBSUPPORT_PARALLEL_FOR_H
#include <algorithm>
#include <type_traits>
#include "gdbsupport/thread-pool.h"
namespace gdb
{
namespace detail
{
/* This is a helper class that is used to accumulate results for
parallel_for. There is a specialization for 'void', below. */
template<typename T>
struct par_for_accumulator
{
public:
explicit par_for_accumulator (size_t n_threads)
: m_futures (n_threads)
{
}
/* The result type that is accumulated. */
typedef std::vector<T> result_type;
/* Post the Ith task to a background thread, and store a future for
later. */
void post (size_t i, std::function<T ()> task)
{
m_futures[i]
= gdb::thread_pool::g_thread_pool->post_task (std::move (task));
}
/* Invoke TASK in the current thread, then compute all the results
from all background tasks and put them into a result vector,
which is returned. */
result_type finish (gdb::function_view<T ()> task)
{
result_type result (m_futures.size () + 1);
result.back () = task ();
for (size_t i = 0; i < m_futures.size (); ++i)
result[i] = m_futures[i].get ();
return result;
}
private:
/* A vector of futures coming from the tasks run in the
background. */
std::vector<gdb::future<T>> m_futures;
};
/* See the generic template. */
template<>
struct par_for_accumulator<void>
{
public:
explicit par_for_accumulator (size_t n_threads)
: m_futures (n_threads)
{
}
/* This specialization does not compute results. */
typedef void result_type;
void post (size_t i, std::function<void ()> task)
{
m_futures[i]
= gdb::thread_pool::g_thread_pool->post_task (std::move (task));
}
result_type finish (gdb::function_view<void ()> task)
{
task ();
for (auto &future : m_futures)
{
/* Use 'get' and not 'wait', to propagate any exception. */
future.get ();
}
}
private:
std::vector<gdb::future<void>> m_futures;
};
}
/* A very simple "parallel for". This splits the range of iterators
into subranges, and then passes each subrange to the callback. The
work may or may not be done in separate threads.
This approach was chosen over having the callback work on single
items because it makes it simple for the caller to do
once-per-subrange initialization and destruction.
The parameter N says how batching ought to be done -- there will be
at least N elements processed per thread. Setting N to 0 is not
allowed.
If the function returns a non-void type, then a vector of the
results is returned. The size of the resulting vector depends on
the number of threads that were used. */
template<class RandomIt, class RangeFunction>
typename gdb::detail::par_for_accumulator<
typename std::result_of<RangeFunction (RandomIt, RandomIt)>::type
>::result_type
parallel_for_each (unsigned n, RandomIt first, RandomIt last,
RangeFunction callback)
{
using result_type
= typename std::result_of<RangeFunction (RandomIt, RandomIt)>::type;
/* If enabled, print debug info about how the work is distributed across
the threads. */
const int parallel_for_each_debug = false;
size_t n_worker_threads = thread_pool::g_thread_pool->thread_count ();
size_t n_threads = n_worker_threads;
size_t n_elements = last - first;
size_t elts_per_thread = 0;
if (n_threads > 1)
{
/* Require that there should be at least N elements in a
thread. */
gdb_assert (n > 0);
if (n_elements / n_threads < n)
n_threads = std::max (n_elements / n, (size_t) 1);
elts_per_thread = n_elements / n_threads;
}
size_t count = n_threads == 0 ? 0 : n_threads - 1;
gdb::detail::par_for_accumulator<result_type> results (count);
if (parallel_for_each_debug)
{
debug_printf (_("Parallel for: n_elements: %zu\n"), n_elements);
debug_printf (_("Parallel for: minimum elements per thread: %u\n"), n);
debug_printf (_("Parallel for: elts_per_thread: %zu\n"), elts_per_thread);
}
for (int i = 0; i < count; ++i)
{
RandomIt end = first + elts_per_thread;
if (parallel_for_each_debug)
debug_printf (_("Parallel for: elements on worker thread %i\t: %zu\n"),
i, (size_t)(end - first));
results.post (i, [=] ()
{
return callback (first, end);
});
first = end;
}
for (int i = count; i < n_worker_threads; ++i)
if (parallel_for_each_debug)
debug_printf (_("Parallel for: elements on worker thread %i\t: 0\n"), i);
/* Process all the remaining elements in the main thread. */
if (parallel_for_each_debug)
debug_printf (_("Parallel for: elements on main thread\t\t: %zu\n"),
(size_t)(last - first));
return results.finish ([=] ()
{
return callback (first, last);
});
}
/* A sequential drop-in replacement of parallel_for_each. This can be useful
when debugging multi-threading behaviour, and you want to limit
multi-threading in a fine-grained way. */
template<class RandomIt, class RangeFunction>
typename gdb::detail::par_for_accumulator<
typename std::result_of<RangeFunction (RandomIt, RandomIt)>::type
>::result_type
sequential_for_each (unsigned n, RandomIt first, RandomIt last,
RangeFunction callback)
{
using result_type
= typename std::result_of<RangeFunction (RandomIt, RandomIt)>::type;
gdb::detail::par_for_accumulator<result_type> results (0);
/* Process all the remaining elements in the main thread. */
return results.finish ([=] ()
{
return callback (first, last);
});
}
}
#endif /* GDBSUPPORT_PARALLEL_FOR_H */
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