Files
kicad-source-mirror/include/priority_thread_pool_task.h
T
John Beard 6cd04bde02 Allegro: multithread zone fill handler for 70% loading speedup (VCU118)
Intersecting and fracturing zone fills takes forever for complex
fills (VCU118 has some fills severa with hundreds of thousands of
points).

However, they are trivially parallelisable - so do that and cut VCU
board load times by 70% - YMMV depending on CPU.

Further save 10% by sorting the heaviest zones first which is nice,
but the real thing to avoid is accidentally scheduling the biggest
zones consecutively on the same thread, which could be a substantial
penalty.

This has the happy effect of reducing the Allegro test suite to under
a minute (VCU118 dominates)
2026-03-10 22:32:20 +08:00

132 lines
4.6 KiB
C++

/*
* This program source code file is part of KiCad, a free EDA CAD application.
*
* Copyright The KiCad Developers, see AUTHORS.txt for contributors.
*
* 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 2
* 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, you may find one here:
* http://www.gnu.org/licenses/old-licenses/gpl-2.0.html
* or you may search the http://www.gnu.org website for the version 2 license,
* or you may write to the Free Software Foundation, Inc.,
* 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA
*/
#pragma once
#include <thread_pool.h>
/**
* A helper class to execute tasks on a thread pool in priority order, with progress reporting.
*/
template <typename ContainerT>
class PRIORITY_THREAD_POOL_TASK
{
public:
using ItemT = typename ContainerT::value_type;
PRIORITY_THREAD_POOL_TASK() :
m_reporter( nullptr ),
m_highestPriority( BS::pr::high ),
m_reporterInterval( std::chrono::milliseconds( 250 ) )
{
}
void SetReporter( PROGRESS_REPORTER* aReporter ) { m_reporter = aReporter; }
/**
* Call this to execute the task on all items in aItems, using the thread pool
* and dispatching the tasks in order of descending priority as determined by
* comparePriority() implemented by the derived class.
*/
void Execute( ContainerT& aItems )
{
thread_pool& tp = GetKiCadThreadPool();
std::vector<std::future<size_t>> returns;
// Compute priority keys paired to item indices
using IndexedPriority = std::pair<size_t, int>;
std::vector<IndexedPriority> indexedKeys( aItems.size() );
for( size_t i = 0; i < aItems.size(); ++i )
{
indexedKeys[i] = { i, computePriorityKey( aItems[i] ) };
}
// Sort by descending priority key
std::sort( indexedKeys.begin(), indexedKeys.end(),
[]( const IndexedPriority& a, const IndexedPriority& b )
{
return a.second > b.second;
} );
// Dispatch largest first
const size_t numItems = aItems.size();
for( size_t priorityRank = 0; priorityRank < numItems; ++priorityRank )
{
const size_t itemIndex = indexedKeys[priorityRank].first;
ItemT& item = aItems[itemIndex];
// Earlier ranking -> higher key -> should be higher priority
const size_t priority = ( ( numItems - priorityRank - 1 ) * m_highestPriority ) / numItems;
returns.emplace_back( tp.submit_task(
[this, &item]
{
return task( item );
},
priority ) );
}
for( const std::future<size_t>& ret : returns )
{
std::future_status status = ret.wait_for( m_reporterInterval );
while( status != std::future_status::ready )
{
if( m_reporter )
m_reporter->KeepRefreshing();
status = ret.wait_for( m_reporterInterval );
}
}
}
protected:
PROGRESS_REPORTER* m_reporter;
private:
/**
* Implement this to compute a priority key for an item.
*
* Return a number representing priority, where a higher number means higher priority.
* The actual values returned don't matter, only their relative order.
*
* (A relational a < b comparator would work too, but a unary key lets us compute it
* once per item in O(n) and then sort indices cheaply, rather than calling it O(n log n)
* times inside std::sort.)
*
* If you'd like to test the effect of this priority ordering, you
* can return a constant value to disable sorting, or return the inverse
* to sort backwards.
*/
virtual int computePriorityKey( const ItemT& aItem ) const = 0;
/**
* Process one item in the thread pool. Return the number of items processed.
*/
virtual size_t task( ItemT& item ) = 0;
BS::priority_t m_highestPriority;
std::chrono::milliseconds m_reporterInterval;
};