283 lines
11 KiB
C++
283 lines
11 KiB
C++
// Copyright 2009-2020 Intel Corporation
|
|
// SPDX-License-Identifier: Apache-2.0
|
|
|
|
#pragma once
|
|
|
|
#include "parallel_for.h"
|
|
#include "../math/range.h"
|
|
|
|
namespace embree
|
|
{
|
|
/* serial partitioning */
|
|
template<typename T, typename V, typename IsLeft, typename Reduction_T>
|
|
__forceinline size_t serial_partitioning(T* array,
|
|
const size_t begin,
|
|
const size_t end,
|
|
V& leftReduction,
|
|
V& rightReduction,
|
|
const IsLeft& is_left,
|
|
const Reduction_T& reduction_t)
|
|
{
|
|
T* l = array + begin;
|
|
T* r = array + end - 1;
|
|
|
|
while(1)
|
|
{
|
|
/* *l < pivot */
|
|
while (likely(l <= r && is_left(*l) ))
|
|
{
|
|
//prefetchw(l+4); // FIXME: enable?
|
|
reduction_t(leftReduction,*l);
|
|
++l;
|
|
}
|
|
/* *r >= pivot) */
|
|
while (likely(l <= r && !is_left(*r)))
|
|
{
|
|
//prefetchw(r-4); FIXME: enable?
|
|
reduction_t(rightReduction,*r);
|
|
--r;
|
|
}
|
|
if (r<l) break;
|
|
|
|
reduction_t(leftReduction ,*r);
|
|
reduction_t(rightReduction,*l);
|
|
xchg(*l,*r);
|
|
l++; r--;
|
|
}
|
|
|
|
return l - array;
|
|
}
|
|
|
|
template<typename T, typename V, typename Vi, typename IsLeft, typename Reduction_T, typename Reduction_V>
|
|
class __aligned(64) parallel_partition_task
|
|
{
|
|
ALIGNED_CLASS_(64);
|
|
private:
|
|
|
|
static const size_t MAX_TASKS = 64;
|
|
|
|
T* array;
|
|
size_t N;
|
|
const IsLeft& is_left;
|
|
const Reduction_T& reduction_t;
|
|
const Reduction_V& reduction_v;
|
|
const Vi& identity;
|
|
|
|
size_t numTasks;
|
|
__aligned(64) size_t counter_start[MAX_TASKS+1];
|
|
__aligned(64) size_t counter_left[MAX_TASKS+1];
|
|
__aligned(64) range<ssize_t> leftMisplacedRanges[MAX_TASKS];
|
|
__aligned(64) range<ssize_t> rightMisplacedRanges[MAX_TASKS];
|
|
__aligned(64) V leftReductions[MAX_TASKS];
|
|
__aligned(64) V rightReductions[MAX_TASKS];
|
|
|
|
public:
|
|
|
|
__forceinline parallel_partition_task(T* array,
|
|
const size_t N,
|
|
const Vi& identity,
|
|
const IsLeft& is_left,
|
|
const Reduction_T& reduction_t,
|
|
const Reduction_V& reduction_v,
|
|
const size_t BLOCK_SIZE)
|
|
|
|
: array(array), N(N), is_left(is_left), reduction_t(reduction_t), reduction_v(reduction_v), identity(identity),
|
|
numTasks(min((N+BLOCK_SIZE-1)/BLOCK_SIZE,min(TaskScheduler::threadCount(),MAX_TASKS))) {}
|
|
|
|
__forceinline const range<ssize_t>* findStartRange(size_t& index, const range<ssize_t>* const r, const size_t numRanges)
|
|
{
|
|
size_t i = 0;
|
|
while(index >= (size_t)r[i].size())
|
|
{
|
|
assert(i < numRanges);
|
|
index -= (size_t)r[i].size();
|
|
i++;
|
|
}
|
|
return &r[i];
|
|
}
|
|
|
|
__forceinline void swapItemsInMisplacedRanges(const size_t numLeftMisplacedRanges,
|
|
const size_t numRightMisplacedRanges,
|
|
const size_t startID,
|
|
const size_t endID)
|
|
{
|
|
size_t leftLocalIndex = startID;
|
|
size_t rightLocalIndex = startID;
|
|
const range<ssize_t>* l_range = findStartRange(leftLocalIndex,leftMisplacedRanges,numLeftMisplacedRanges);
|
|
const range<ssize_t>* r_range = findStartRange(rightLocalIndex,rightMisplacedRanges,numRightMisplacedRanges);
|
|
|
|
size_t l_left = l_range->size() - leftLocalIndex;
|
|
size_t r_left = r_range->size() - rightLocalIndex;
|
|
T *__restrict__ l = &array[l_range->begin() + leftLocalIndex];
|
|
T *__restrict__ r = &array[r_range->begin() + rightLocalIndex];
|
|
size_t size = endID - startID;
|
|
size_t items = min(size,min(l_left,r_left));
|
|
|
|
while (size)
|
|
{
|
|
if (unlikely(l_left == 0))
|
|
{
|
|
l_range++;
|
|
l_left = l_range->size();
|
|
l = &array[l_range->begin()];
|
|
items = min(size,min(l_left,r_left));
|
|
}
|
|
|
|
if (unlikely(r_left == 0))
|
|
{
|
|
r_range++;
|
|
r_left = r_range->size();
|
|
r = &array[r_range->begin()];
|
|
items = min(size,min(l_left,r_left));
|
|
}
|
|
|
|
size -= items;
|
|
l_left -= items;
|
|
r_left -= items;
|
|
|
|
while(items) {
|
|
items--;
|
|
xchg(*l++,*r++);
|
|
}
|
|
}
|
|
}
|
|
|
|
__forceinline size_t partition(V& leftReduction, V& rightReduction)
|
|
{
|
|
/* partition the individual ranges for each task */
|
|
parallel_for(numTasks,[&] (const size_t taskID) {
|
|
const size_t startID = (taskID+0)*N/numTasks;
|
|
const size_t endID = (taskID+1)*N/numTasks;
|
|
V local_left(identity);
|
|
V local_right(identity);
|
|
const size_t mid = serial_partitioning(array,startID,endID,local_left,local_right,is_left,reduction_t);
|
|
counter_start[taskID] = startID;
|
|
counter_left [taskID] = mid-startID;
|
|
leftReductions[taskID] = local_left;
|
|
rightReductions[taskID] = local_right;
|
|
});
|
|
counter_start[numTasks] = N;
|
|
counter_left[numTasks] = 0;
|
|
|
|
/* finalize the reductions */
|
|
for (size_t i=0; i<numTasks; i++) {
|
|
reduction_v(leftReduction,leftReductions[i]);
|
|
reduction_v(rightReduction,rightReductions[i]);
|
|
}
|
|
|
|
/* calculate mid point for partitioning */
|
|
size_t mid = counter_left[0];
|
|
for (size_t i=1; i<numTasks; i++)
|
|
mid += counter_left[i];
|
|
const range<ssize_t> globalLeft (0,mid);
|
|
const range<ssize_t> globalRight(mid,N);
|
|
|
|
/* calculate all left and right ranges that are on the wrong global side */
|
|
size_t numMisplacedRangesLeft = 0;
|
|
size_t numMisplacedRangesRight = 0;
|
|
size_t numMisplacedItemsLeft = 0;
|
|
size_t numMisplacedItemsRight = 0;
|
|
|
|
for (size_t i=0; i<numTasks; i++)
|
|
{
|
|
const range<ssize_t> left_range (counter_start[i], counter_start[i] + counter_left[i]);
|
|
const range<ssize_t> right_range(counter_start[i] + counter_left[i], counter_start[i+1]);
|
|
const range<ssize_t> left_misplaced = globalLeft. intersect(right_range);
|
|
const range<ssize_t> right_misplaced = globalRight.intersect(left_range);
|
|
|
|
if (!left_misplaced.empty())
|
|
{
|
|
numMisplacedItemsLeft += left_misplaced.size();
|
|
leftMisplacedRanges[numMisplacedRangesLeft++] = left_misplaced;
|
|
}
|
|
|
|
if (!right_misplaced.empty())
|
|
{
|
|
numMisplacedItemsRight += right_misplaced.size();
|
|
rightMisplacedRanges[numMisplacedRangesRight++] = right_misplaced;
|
|
}
|
|
}
|
|
assert( numMisplacedItemsLeft == numMisplacedItemsRight );
|
|
|
|
/* if no items are misplaced we are done */
|
|
if (numMisplacedItemsLeft == 0)
|
|
return mid;
|
|
|
|
/* otherwise we copy the items to the right place in parallel */
|
|
parallel_for(numTasks,[&] (const size_t taskID) {
|
|
const size_t startID = (taskID+0)*numMisplacedItemsLeft/numTasks;
|
|
const size_t endID = (taskID+1)*numMisplacedItemsLeft/numTasks;
|
|
swapItemsInMisplacedRanges(numMisplacedRangesLeft,numMisplacedRangesRight,startID,endID);
|
|
});
|
|
|
|
return mid;
|
|
}
|
|
};
|
|
|
|
template<typename T, typename V, typename Vi, typename IsLeft, typename Reduction_T, typename Reduction_V>
|
|
__noinline size_t parallel_partitioning(T* array,
|
|
const size_t begin,
|
|
const size_t end,
|
|
const Vi &identity,
|
|
V &leftReduction,
|
|
V &rightReduction,
|
|
const IsLeft& is_left,
|
|
const Reduction_T& reduction_t,
|
|
const Reduction_V& reduction_v,
|
|
size_t BLOCK_SIZE = 128)
|
|
{
|
|
/* fall back to single threaded partitioning for small N */
|
|
if (unlikely(end-begin < BLOCK_SIZE))
|
|
return serial_partitioning(array,begin,end,leftReduction,rightReduction,is_left,reduction_t);
|
|
|
|
/* otherwise use parallel code */
|
|
else {
|
|
typedef parallel_partition_task<T,V,Vi,IsLeft,Reduction_T,Reduction_V> partition_task;
|
|
std::unique_ptr<partition_task> p(new partition_task(&array[begin],end-begin,identity,is_left,reduction_t,reduction_v,BLOCK_SIZE));
|
|
return begin+p->partition(leftReduction,rightReduction);
|
|
}
|
|
}
|
|
|
|
template<typename T, typename V, typename Vi, typename IsLeft, typename Reduction_T, typename Reduction_V>
|
|
__noinline size_t parallel_partitioning(T* array,
|
|
const size_t begin,
|
|
const size_t end,
|
|
const Vi &identity,
|
|
V &leftReduction,
|
|
V &rightReduction,
|
|
const IsLeft& is_left,
|
|
const Reduction_T& reduction_t,
|
|
const Reduction_V& reduction_v,
|
|
size_t BLOCK_SIZE,
|
|
size_t PARALLEL_THRESHOLD)
|
|
{
|
|
/* fall back to single threaded partitioning for small N */
|
|
if (unlikely(end-begin < PARALLEL_THRESHOLD))
|
|
return serial_partitioning(array,begin,end,leftReduction,rightReduction,is_left,reduction_t);
|
|
|
|
/* otherwise use parallel code */
|
|
else {
|
|
typedef parallel_partition_task<T,V,Vi,IsLeft,Reduction_T,Reduction_V> partition_task;
|
|
std::unique_ptr<partition_task> p(new partition_task(&array[begin],end-begin,identity,is_left,reduction_t,reduction_v,BLOCK_SIZE));
|
|
return begin+p->partition(leftReduction,rightReduction);
|
|
}
|
|
}
|
|
|
|
|
|
template<typename T, typename IsLeft>
|
|
inline size_t parallel_partitioning(T* array,
|
|
const size_t begin,
|
|
const size_t end,
|
|
const IsLeft& is_left,
|
|
size_t BLOCK_SIZE = 128)
|
|
{
|
|
size_t leftReduction = 0;
|
|
size_t rightReduction = 0;
|
|
return parallel_partitioning(
|
|
array,begin,end,0,leftReduction,rightReduction,is_left,
|
|
[] (size_t& t,const T& ref) { },
|
|
[] (size_t& t0,size_t& t1) { },
|
|
BLOCK_SIZE);
|
|
}
|
|
|
|
}
|