godot/thirdparty/embree/kernels/builders/bvh_builder_sah.h
jfons 767e374dce Upgrade Embree to the latest official release.
Since Embree v3.13.0 supports AARCH64, switch back to the
official repo instead of using Embree-aarch64.

`thirdparty/embree/patches/godot-changes.patch` should now contain
an accurate diff of the changes done to the library.
2021-05-21 17:00:24 +02:00

670 lines
27 KiB
C++

// Copyright 2009-2021 Intel Corporation
// SPDX-License-Identifier: Apache-2.0
#pragma once
#include "heuristic_binning_array_aligned.h"
#include "heuristic_spatial_array.h"
#include "heuristic_openmerge_array.h"
#if defined(__AVX512F__) && !defined(__AVX512VL__) // KNL
# define NUM_OBJECT_BINS 16
# define NUM_SPATIAL_BINS 16
#else
# define NUM_OBJECT_BINS 32
# define NUM_SPATIAL_BINS 16
#endif
namespace embree
{
namespace isa
{
MAYBE_UNUSED static const float travCost = 1.0f;
MAYBE_UNUSED static const size_t DEFAULT_SINGLE_THREAD_THRESHOLD = 1024;
struct GeneralBVHBuilder
{
static const size_t MAX_BRANCHING_FACTOR = 16; //!< maximum supported BVH branching factor
static const size_t MIN_LARGE_LEAF_LEVELS = 8; //!< create balanced tree of we are that many levels before the maximum tree depth
/*! settings for SAH builder */
struct Settings
{
/*! default settings */
Settings ()
: branchingFactor(2), maxDepth(32), logBlockSize(0), minLeafSize(1), maxLeafSize(7),
travCost(1.0f), intCost(1.0f), singleThreadThreshold(1024), primrefarrayalloc(inf) {}
/*! initialize settings from API settings */
Settings (const RTCBuildArguments& settings)
: branchingFactor(2), maxDepth(32), logBlockSize(0), minLeafSize(1), maxLeafSize(7),
travCost(1.0f), intCost(1.0f), singleThreadThreshold(1024), primrefarrayalloc(inf)
{
if (RTC_BUILD_ARGUMENTS_HAS(settings,maxBranchingFactor)) branchingFactor = settings.maxBranchingFactor;
if (RTC_BUILD_ARGUMENTS_HAS(settings,maxDepth )) maxDepth = settings.maxDepth;
if (RTC_BUILD_ARGUMENTS_HAS(settings,sahBlockSize )) logBlockSize = bsr(settings.sahBlockSize);
if (RTC_BUILD_ARGUMENTS_HAS(settings,minLeafSize )) minLeafSize = settings.minLeafSize;
if (RTC_BUILD_ARGUMENTS_HAS(settings,maxLeafSize )) maxLeafSize = settings.maxLeafSize;
if (RTC_BUILD_ARGUMENTS_HAS(settings,traversalCost )) travCost = settings.traversalCost;
if (RTC_BUILD_ARGUMENTS_HAS(settings,intersectionCost )) intCost = settings.intersectionCost;
minLeafSize = min(minLeafSize,maxLeafSize);
}
Settings (size_t sahBlockSize, size_t minLeafSize, size_t maxLeafSize, float travCost, float intCost, size_t singleThreadThreshold, size_t primrefarrayalloc = inf)
: branchingFactor(2), maxDepth(32), logBlockSize(bsr(sahBlockSize)), minLeafSize(minLeafSize), maxLeafSize(maxLeafSize),
travCost(travCost), intCost(intCost), singleThreadThreshold(singleThreadThreshold), primrefarrayalloc(primrefarrayalloc)
{
minLeafSize = min(minLeafSize,maxLeafSize);
}
public:
size_t branchingFactor; //!< branching factor of BVH to build
size_t maxDepth; //!< maximum depth of BVH to build
size_t logBlockSize; //!< log2 of blocksize for SAH heuristic
size_t minLeafSize; //!< minimum size of a leaf
size_t maxLeafSize; //!< maximum size of a leaf
float travCost; //!< estimated cost of one traversal step
float intCost; //!< estimated cost of one primitive intersection
size_t singleThreadThreshold; //!< threshold when we switch to single threaded build
size_t primrefarrayalloc; //!< builder uses prim ref array to allocate nodes and leaves when a subtree of that size is finished
};
/*! recursive state of builder */
template<typename Set, typename Split>
struct BuildRecordT
{
public:
__forceinline BuildRecordT () {}
__forceinline BuildRecordT (size_t depth)
: depth(depth), alloc_barrier(false), prims(empty) {}
__forceinline BuildRecordT (size_t depth, const Set& prims)
: depth(depth), alloc_barrier(false), prims(prims) {}
__forceinline BBox3fa bounds() const { return prims.geomBounds; }
__forceinline friend bool operator< (const BuildRecordT& a, const BuildRecordT& b) { return a.prims.size() < b.prims.size(); }
__forceinline friend bool operator> (const BuildRecordT& a, const BuildRecordT& b) { return a.prims.size() > b.prims.size(); }
__forceinline size_t size() const { return prims.size(); }
public:
size_t depth; //!< Depth of the root of this subtree.
bool alloc_barrier; //!< barrier used to reuse primref-array blocks to allocate nodes
Set prims; //!< The list of primitives.
};
template<typename PrimRef, typename Set>
struct DefaultCanCreateLeafFunc
{
__forceinline bool operator()(const PrimRef*, const Set&) const { return true; }
};
template<typename PrimRef, typename Set>
struct DefaultCanCreateLeafSplitFunc
{
__forceinline void operator()(PrimRef*, const Set&, Set&, Set&) const { }
};
template<typename BuildRecord,
typename Heuristic,
typename Set,
typename PrimRef,
typename ReductionTy,
typename Allocator,
typename CreateAllocFunc,
typename CreateNodeFunc,
typename UpdateNodeFunc,
typename CreateLeafFunc,
typename CanCreateLeafFunc,
typename CanCreateLeafSplitFunc,
typename ProgressMonitor>
class BuilderT
{
friend struct GeneralBVHBuilder;
BuilderT (PrimRef* prims,
Heuristic& heuristic,
const CreateAllocFunc& createAlloc,
const CreateNodeFunc& createNode,
const UpdateNodeFunc& updateNode,
const CreateLeafFunc& createLeaf,
const CanCreateLeafFunc& canCreateLeaf,
const CanCreateLeafSplitFunc& canCreateLeafSplit,
const ProgressMonitor& progressMonitor,
const Settings& settings) :
cfg(settings),
prims(prims),
heuristic(heuristic),
createAlloc(createAlloc),
createNode(createNode),
updateNode(updateNode),
createLeaf(createLeaf),
canCreateLeaf(canCreateLeaf),
canCreateLeafSplit(canCreateLeafSplit),
progressMonitor(progressMonitor)
{
if (cfg.branchingFactor > MAX_BRANCHING_FACTOR)
throw_RTCError(RTC_ERROR_UNKNOWN,"bvh_builder: branching factor too large");
}
const ReductionTy createLargeLeaf(const BuildRecord& current, Allocator alloc)
{
/* this should never occur but is a fatal error */
if (current.depth > cfg.maxDepth)
throw_RTCError(RTC_ERROR_UNKNOWN,"depth limit reached");
/* create leaf for few primitives */
if (current.prims.size() <= cfg.maxLeafSize && canCreateLeaf(prims,current.prims))
return createLeaf(prims,current.prims,alloc);
/* fill all children by always splitting the largest one */
ReductionTy values[MAX_BRANCHING_FACTOR];
BuildRecord children[MAX_BRANCHING_FACTOR];
size_t numChildren = 1;
children[0] = current;
do {
/* find best child with largest bounding box area */
size_t bestChild = -1;
size_t bestSize = 0;
for (size_t i=0; i<numChildren; i++)
{
/* ignore leaves as they cannot get split */
if (children[i].prims.size() <= cfg.maxLeafSize && canCreateLeaf(prims,children[i].prims))
continue;
/* remember child with largest size */
if (children[i].prims.size() > bestSize) {
bestSize = children[i].prims.size();
bestChild = i;
}
}
if (bestChild == (size_t)-1) break;
/*! split best child into left and right child */
BuildRecord left(current.depth+1);
BuildRecord right(current.depth+1);
if (!canCreateLeaf(prims,children[bestChild].prims)) {
canCreateLeafSplit(prims,children[bestChild].prims,left.prims,right.prims);
} else {
heuristic.splitFallback(children[bestChild].prims,left.prims,right.prims);
}
/* add new children left and right */
children[bestChild] = children[numChildren-1];
children[numChildren-1] = left;
children[numChildren+0] = right;
numChildren++;
} while (numChildren < cfg.branchingFactor);
/* set barrier for primrefarrayalloc */
if (unlikely(current.size() > cfg.primrefarrayalloc))
for (size_t i=0; i<numChildren; i++)
children[i].alloc_barrier = children[i].size() <= cfg.primrefarrayalloc;
/* create node */
auto node = createNode(children,numChildren,alloc);
/* recurse into each child and perform reduction */
for (size_t i=0; i<numChildren; i++)
values[i] = createLargeLeaf(children[i],alloc);
/* perform reduction */
return updateNode(current,children,node,values,numChildren);
}
const ReductionTy recurse(BuildRecord& current, Allocator alloc, bool toplevel)
{
/* get thread local allocator */
if (!alloc)
alloc = createAlloc();
/* call memory monitor function to signal progress */
if (toplevel && current.size() <= cfg.singleThreadThreshold)
progressMonitor(current.size());
/*! find best split */
auto split = heuristic.find(current.prims,cfg.logBlockSize);
/*! compute leaf and split cost */
const float leafSAH = cfg.intCost*current.prims.leafSAH(cfg.logBlockSize);
const float splitSAH = cfg.travCost*halfArea(current.prims.geomBounds)+cfg.intCost*split.splitSAH();
assert((current.prims.size() == 0) || ((leafSAH >= 0) && (splitSAH >= 0)));
/*! create a leaf node when threshold reached or SAH tells us to stop */
if (current.prims.size() <= cfg.minLeafSize || current.depth+MIN_LARGE_LEAF_LEVELS >= cfg.maxDepth || (current.prims.size() <= cfg.maxLeafSize && leafSAH <= splitSAH)) {
heuristic.deterministic_order(current.prims);
return createLargeLeaf(current,alloc);
}
/*! perform initial split */
Set lprims,rprims;
heuristic.split(split,current.prims,lprims,rprims);
/*! initialize child list with initial split */
ReductionTy values[MAX_BRANCHING_FACTOR];
BuildRecord children[MAX_BRANCHING_FACTOR];
children[0] = BuildRecord(current.depth+1,lprims);
children[1] = BuildRecord(current.depth+1,rprims);
size_t numChildren = 2;
/*! split until node is full or SAH tells us to stop */
while (numChildren < cfg.branchingFactor)
{
/*! find best child to split */
float bestArea = neg_inf;
ssize_t bestChild = -1;
for (size_t i=0; i<numChildren; i++)
{
/* ignore leaves as they cannot get split */
if (children[i].prims.size() <= cfg.minLeafSize) continue;
/* find child with largest surface area */
if (halfArea(children[i].prims.geomBounds) > bestArea) {
bestChild = i;
bestArea = halfArea(children[i].prims.geomBounds);
}
}
if (bestChild == -1) break;
/* perform best found split */
BuildRecord& brecord = children[bestChild];
BuildRecord lrecord(current.depth+1);
BuildRecord rrecord(current.depth+1);
auto split = heuristic.find(brecord.prims,cfg.logBlockSize);
heuristic.split(split,brecord.prims,lrecord.prims,rrecord.prims);
children[bestChild ] = lrecord;
children[numChildren] = rrecord;
numChildren++;
}
/* set barrier for primrefarrayalloc */
if (unlikely(current.size() > cfg.primrefarrayalloc))
for (size_t i=0; i<numChildren; i++)
children[i].alloc_barrier = children[i].size() <= cfg.primrefarrayalloc;
/* sort buildrecords for faster shadow ray traversal */
std::sort(&children[0],&children[numChildren],std::greater<BuildRecord>());
/*! create an inner node */
auto node = createNode(children,numChildren,alloc);
/* spawn tasks */
if (current.size() > cfg.singleThreadThreshold)
{
/*! parallel_for is faster than spawing sub-tasks */
parallel_for(size_t(0), numChildren, [&] (const range<size_t>& r) { // FIXME: no range here
for (size_t i=r.begin(); i<r.end(); i++) {
values[i] = recurse(children[i],nullptr,true);
_mm_mfence(); // to allow non-temporal stores during build
}
});
return updateNode(current,children,node,values,numChildren);
}
/* recurse into each child */
else
{
for (size_t i=0; i<numChildren; i++)
values[i] = recurse(children[i],alloc,false);
return updateNode(current,children,node,values,numChildren);
}
}
private:
Settings cfg;
PrimRef* prims;
Heuristic& heuristic;
const CreateAllocFunc& createAlloc;
const CreateNodeFunc& createNode;
const UpdateNodeFunc& updateNode;
const CreateLeafFunc& createLeaf;
const CanCreateLeafFunc& canCreateLeaf;
const CanCreateLeafSplitFunc& canCreateLeafSplit;
const ProgressMonitor& progressMonitor;
};
template<
typename ReductionTy,
typename Heuristic,
typename Set,
typename PrimRef,
typename CreateAllocFunc,
typename CreateNodeFunc,
typename UpdateNodeFunc,
typename CreateLeafFunc,
typename ProgressMonitor>
__noinline static ReductionTy build(Heuristic& heuristic,
PrimRef* prims,
const Set& set,
CreateAllocFunc createAlloc,
CreateNodeFunc createNode, UpdateNodeFunc updateNode,
const CreateLeafFunc& createLeaf,
const ProgressMonitor& progressMonitor,
const Settings& settings)
{
typedef BuildRecordT<Set,typename Heuristic::Split> BuildRecord;
typedef BuilderT<
BuildRecord,
Heuristic,
Set,
PrimRef,
ReductionTy,
decltype(createAlloc()),
CreateAllocFunc,
CreateNodeFunc,
UpdateNodeFunc,
CreateLeafFunc,
DefaultCanCreateLeafFunc<PrimRef, Set>,
DefaultCanCreateLeafSplitFunc<PrimRef, Set>,
ProgressMonitor> Builder;
/* instantiate builder */
Builder builder(prims,
heuristic,
createAlloc,
createNode,
updateNode,
createLeaf,
DefaultCanCreateLeafFunc<PrimRef, Set>(),
DefaultCanCreateLeafSplitFunc<PrimRef, Set>(),
progressMonitor,
settings);
/* build hierarchy */
BuildRecord record(1,set);
const ReductionTy root = builder.recurse(record,nullptr,true);
_mm_mfence(); // to allow non-temporal stores during build
return root;
}
template<
typename ReductionTy,
typename Heuristic,
typename Set,
typename PrimRef,
typename CreateAllocFunc,
typename CreateNodeFunc,
typename UpdateNodeFunc,
typename CreateLeafFunc,
typename CanCreateLeafFunc,
typename CanCreateLeafSplitFunc,
typename ProgressMonitor>
__noinline static ReductionTy build(Heuristic& heuristic,
PrimRef* prims,
const Set& set,
CreateAllocFunc createAlloc,
CreateNodeFunc createNode, UpdateNodeFunc updateNode,
const CreateLeafFunc& createLeaf,
const CanCreateLeafFunc& canCreateLeaf,
const CanCreateLeafSplitFunc& canCreateLeafSplit,
const ProgressMonitor& progressMonitor,
const Settings& settings)
{
typedef BuildRecordT<Set,typename Heuristic::Split> BuildRecord;
typedef BuilderT<
BuildRecord,
Heuristic,
Set,
PrimRef,
ReductionTy,
decltype(createAlloc()),
CreateAllocFunc,
CreateNodeFunc,
UpdateNodeFunc,
CreateLeafFunc,
CanCreateLeafFunc,
CanCreateLeafSplitFunc,
ProgressMonitor> Builder;
/* instantiate builder */
Builder builder(prims,
heuristic,
createAlloc,
createNode,
updateNode,
createLeaf,
canCreateLeaf,
canCreateLeafSplit,
progressMonitor,
settings);
/* build hierarchy */
BuildRecord record(1,set);
const ReductionTy root = builder.recurse(record,nullptr,true);
_mm_mfence(); // to allow non-temporal stores during build
return root;
}
};
/* SAH builder that operates on an array of BuildRecords */
struct BVHBuilderBinnedSAH
{
typedef PrimInfoRange Set;
typedef HeuristicArrayBinningSAH<PrimRef,NUM_OBJECT_BINS> Heuristic;
typedef GeneralBVHBuilder::BuildRecordT<Set,typename Heuristic::Split> BuildRecord;
typedef GeneralBVHBuilder::Settings Settings;
/*! special builder that propagates reduction over the tree */
template<
typename ReductionTy,
typename CreateAllocFunc,
typename CreateNodeFunc,
typename UpdateNodeFunc,
typename CreateLeafFunc,
typename ProgressMonitor>
static ReductionTy build(CreateAllocFunc createAlloc,
CreateNodeFunc createNode, UpdateNodeFunc updateNode,
const CreateLeafFunc& createLeaf,
const ProgressMonitor& progressMonitor,
PrimRef* prims, const PrimInfo& pinfo,
const Settings& settings)
{
Heuristic heuristic(prims);
return GeneralBVHBuilder::build<ReductionTy,Heuristic,Set,PrimRef>(
heuristic,
prims,
PrimInfoRange(0,pinfo.size(),pinfo),
createAlloc,
createNode,
updateNode,
createLeaf,
progressMonitor,
settings);
}
/*! special builder that propagates reduction over the tree */
template<
typename ReductionTy,
typename CreateAllocFunc,
typename CreateNodeFunc,
typename UpdateNodeFunc,
typename CreateLeafFunc,
typename CanCreateLeafFunc,
typename CanCreateLeafSplitFunc,
typename ProgressMonitor>
static ReductionTy build(CreateAllocFunc createAlloc,
CreateNodeFunc createNode, UpdateNodeFunc updateNode,
const CreateLeafFunc& createLeaf,
const CanCreateLeafFunc& canCreateLeaf,
const CanCreateLeafSplitFunc& canCreateLeafSplit,
const ProgressMonitor& progressMonitor,
PrimRef* prims, const PrimInfo& pinfo,
const Settings& settings)
{
Heuristic heuristic(prims);
return GeneralBVHBuilder::build<ReductionTy,Heuristic,Set,PrimRef>(
heuristic,
prims,
PrimInfoRange(0,pinfo.size(),pinfo),
createAlloc,
createNode,
updateNode,
createLeaf,
canCreateLeaf,
canCreateLeafSplit,
progressMonitor,
settings);
}
};
/* Spatial SAH builder that operates on an double-buffered array of BuildRecords */
struct BVHBuilderBinnedFastSpatialSAH
{
typedef PrimInfoExtRange Set;
typedef Split2<BinSplit<NUM_OBJECT_BINS>,SpatialBinSplit<NUM_SPATIAL_BINS> > Split;
typedef GeneralBVHBuilder::BuildRecordT<Set,Split> BuildRecord;
typedef GeneralBVHBuilder::Settings Settings;
static const unsigned int GEOMID_MASK = 0xFFFFFFFF >> RESERVED_NUM_SPATIAL_SPLITS_GEOMID_BITS;
static const unsigned int SPLITS_MASK = 0xFFFFFFFF << (32-RESERVED_NUM_SPATIAL_SPLITS_GEOMID_BITS);
template<typename ReductionTy, typename UserCreateLeaf>
struct CreateLeafExt
{
__forceinline CreateLeafExt (const UserCreateLeaf userCreateLeaf)
: userCreateLeaf(userCreateLeaf) {}
// __noinline is workaround for ICC2016 compiler bug
template<typename Allocator>
__noinline ReductionTy operator() (PrimRef* prims, const range<size_t>& range, Allocator alloc) const
{
for (size_t i=range.begin(); i<range.end(); i++)
prims[i].lower.u &= GEOMID_MASK;
return userCreateLeaf(prims,range,alloc);
}
const UserCreateLeaf userCreateLeaf;
};
/*! special builder that propagates reduction over the tree */
template<
typename ReductionTy,
typename CreateAllocFunc,
typename CreateNodeFunc,
typename UpdateNodeFunc,
typename CreateLeafFunc,
typename SplitPrimitiveFunc,
typename ProgressMonitor>
static ReductionTy build(CreateAllocFunc createAlloc,
CreateNodeFunc createNode,
UpdateNodeFunc updateNode,
const CreateLeafFunc& createLeaf,
SplitPrimitiveFunc splitPrimitive,
ProgressMonitor progressMonitor,
PrimRef* prims,
const size_t extSize,
const PrimInfo& pinfo,
const Settings& settings)
{
typedef HeuristicArraySpatialSAH<SplitPrimitiveFunc,PrimRef,NUM_OBJECT_BINS,NUM_SPATIAL_BINS> Heuristic;
Heuristic heuristic(splitPrimitive,prims,pinfo);
/* calculate total surface area */ // FIXME: this sum is not deterministic
const float A = (float) parallel_reduce(size_t(0),pinfo.size(),0.0, [&] (const range<size_t>& r) -> double {
double A = 0.0f;
for (size_t i=r.begin(); i<r.end(); i++)
{
PrimRef& prim = prims[i];
A += area(prim.bounds());
}
return A;
},std::plus<double>());
/* calculate maximum number of spatial splits per primitive */
const unsigned int maxSplits = ((size_t)1 << RESERVED_NUM_SPATIAL_SPLITS_GEOMID_BITS)-1;
const float f = 10.0f;
const float invA = 1.0f / A;
parallel_for( size_t(0), pinfo.size(), [&](const range<size_t>& r) {
for (size_t i=r.begin(); i<r.end(); i++)
{
PrimRef& prim = prims[i];
assert((prim.geomID() & SPLITS_MASK) == 0);
// FIXME: is there a better general heuristic ?
const float nf = ceilf(f*pinfo.size()*area(prim.bounds()) * invA);
unsigned int n = 4+min((int)maxSplits-4, max(1, (int)(nf)));
prim.lower.u |= n << (32-RESERVED_NUM_SPATIAL_SPLITS_GEOMID_BITS);
}
});
return GeneralBVHBuilder::build<ReductionTy,Heuristic,Set,PrimRef>(
heuristic,
prims,
PrimInfoExtRange(0,pinfo.size(),extSize,pinfo),
createAlloc,
createNode,
updateNode,
CreateLeafExt<ReductionTy,CreateLeafFunc>(createLeaf),
progressMonitor,
settings);
}
};
/* Open/Merge SAH builder that operates on an array of BuildRecords */
struct BVHBuilderBinnedOpenMergeSAH
{
static const size_t NUM_OBJECT_BINS_HQ = 32;
typedef PrimInfoExtRange Set;
typedef BinSplit<NUM_OBJECT_BINS_HQ> Split;
typedef GeneralBVHBuilder::BuildRecordT<Set,Split> BuildRecord;
typedef GeneralBVHBuilder::Settings Settings;
/*! special builder that propagates reduction over the tree */
template<
typename ReductionTy,
typename BuildRef,
typename CreateAllocFunc,
typename CreateNodeFunc,
typename UpdateNodeFunc,
typename CreateLeafFunc,
typename NodeOpenerFunc,
typename ProgressMonitor>
static ReductionTy build(CreateAllocFunc createAlloc,
CreateNodeFunc createNode,
UpdateNodeFunc updateNode,
const CreateLeafFunc& createLeaf,
NodeOpenerFunc nodeOpenerFunc,
ProgressMonitor progressMonitor,
BuildRef* prims,
const size_t extSize,
const PrimInfo& pinfo,
const Settings& settings)
{
typedef HeuristicArrayOpenMergeSAH<NodeOpenerFunc,BuildRef,NUM_OBJECT_BINS_HQ> Heuristic;
Heuristic heuristic(nodeOpenerFunc,prims,settings.branchingFactor);
return GeneralBVHBuilder::build<ReductionTy,Heuristic,Set,BuildRef>(
heuristic,
prims,
PrimInfoExtRange(0,pinfo.size(),extSize,pinfo),
createAlloc,
createNode,
updateNode,
createLeaf,
progressMonitor,
settings);
}
};
}
}