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