Upload
gervais-griffith
View
215
Download
0
Embed Size (px)
Citation preview
Fast BVH Construction on GPUs(Eurographics 2009)
Park, Soonchan
KAIST (Korea Advanced Institute of Science and Technology)
2
Contents
● What is BVH● Motivation● Three Algorithm to Construct BVH
● LBVH● SAH Hierarchy Construction● Hybrid GPU Construction Algorithm
● Results & Analysis
3
Contents
● What is BVH● Motivation● Three Algorithm to Construct BVH
● LBVH● SAH Hierarchy Construction● Hybrid GPU Construction Algorithm
● Results & Analysis
4
What is BVH?
● Bounding Volume Hierarchy● A tree structure on a set of geometric
objects● “Fast Computation”
● Ray tracing ● Collision detection● Visibility Culling
5
What is BVH?
● Issues of BVH construction● Construction Time● Effectiveness of Construction
●How much improvement BVH makes– Median Subdivision & Surface Area Heuristic
6
Motivation
● BVH Construction
Almost all prior works are about “Purely serial construction algorithms”
Make Efficient Parallel algorithms! on manycore processors
How to make processes of BVH construction appropriate for parallel computation
7
Contents
● What is BVH● Motivation● Three Algorithm to Construct BVH
● LBVH● SAH Hierarchy Construction● Hybrid GPU Construction Algorithm
● Results & Analysis
8
Contents
● What is BVH● Motivation● Three Algorithm to Construct BVH
● LBVH● SAH Hierarchy Construction● Hybrid GPU Construction Algorithm
● Results & Analysis
9
LBVH
● Linear Bounding Volume Hierarchy● Simplest approach to parallelizing BVH
Construction● Sorting input primitives by Morton Codes● BVH Construction Sorting ( O(nlogn) )
10
Morton Codes (Z-order)
● Space-filling curve
● Morton Codes (Z-order)● Good locality-preserving● Express space as bits
11
Morton Codes (Z-order)
12
LBVH
● Linear B.V.H.● Sorting primitives
along the curveparallel radix sort[SHG08]
● Each primitive hasbit expression of position
● How to makethe Hierarchy?
13
LBVH
● Make Hierarchy● Test all Primitive i with Primitive i+1
●What levels they are separated●Make list ( (Primitive index) , ( separate level) )
● Resort the list by level
We can have intervals at each level!
14
Example
(6, 1)
(3, 2) (6, 2)
(2,3) (3,3) (4,3) (5,3) (6,3) (7,3)
(1,4) (2,4) (3,4) (4,4) (5,4) (6,4) (7,4)
Split list (Prim.Index, Separate Lev.)
15
7 81 2 3 4 5 6 LEVEL 1
1 2 3 4 5 6 7 8
16
7 81 2 3 4 5 6
123 456
LEVEL 1
LEVEL 2
1 2 3 4 5 6 7 8
17
7 81 2 3 4 5 6
123 456
312 4 5 6 7 8
LEVEL 1
LEVEL 2
LEVEL 3
1 2 3 4 5 6 7 8
18
7 81 2 3 4 5 6
123 456
312 4 5 6 7 8
1 2
LEVEL 1
LEVEL 2
LEVEL 3
LEVEL 4
1 2 3 4 5 6 7 8
19
20
LBVH
● Pros● Very fast – same complexity as sorting
●+ we use parallel radix sort [SHG 08]● Cons
● Constructed Hierarchy is not optimized●It uniformly subdivides space at the median
● Leaf can has multiple primitives
21
Contents
● What is BVH● Motivation● Three Algorithm to Construct BVH
● LBVH● SAH Hierarchy Construction● Hybrid GPU Construction Algorithm
● Results & Analysis
22
What is SAH
● Surface Area Heuristic● Answer for optimized architecture
●“which of a number of partitions of primitives will be better?●“which of a number of possible positions to split space will be better?”
23
What is SAH
● SAH optimized construction can also be achieved in O(nlogn) [WH06]
● Processes for SAH● Recursively splitting the set of geometric
primitives (usually two parts per step-binary tree)
● Evaluate with “cost function” ●Cost function can be defined
● Find the one with lowest cost● Check all possible split position can be
costly● Sampling method can be applied
24
GPU SAH Construction
● Breadth-first construction using work queues
● Parallelization!
Input queue
Output queue
Output queue
25
Data-Parallel SAH Split
● Two steps for performing SAH split● Determine the best split position by
evaluating the SAH● Reorder the primitives ( corresponds to
the new split )
26
Data-Parallel SAH Split
● Determine the best split position● Approximate SAH computation● Generate k uniformly sampled split
candidates for three axes ( test all the samples in parallel by using 3k threads )
● Each thread computes the SAH cost for its split candidate
● Find split candidate with lowest cost● Reorder the Primitives
● In corresponds to the new splits● Only reorder the indices
●No copy of geometry
27
Small Split Operation
● Two main bottleneck● Initial split at the top level of hierarchy is very
slow ● Large # of primitives at Top level
– By using hybrid method (discussed later)● Large # of small splits at Low level
● Problems●Higher compaction costs generated by large # of splits●Vector utilizing is low (Few primitive per split)
● Large # of small size of split makes problem Use different split kernel for small size
28
Small Split Operation
● Main Idea● Set Thresh hold to define “Small split”
●Depends on geometry data & cache size (32)
● Use processor’s local memory●to maintain a local work queue●Keep all the geometric primitives
● Pros● Reduce memory bandwidth● Decrease # of Thread
●Maximize utilization of vector operation● Avoid waiting for memory access
15~20% speed up
29
Small Split Operation
Times# of
active splits
Level of splits
30
Contents
● What is BVH● Motivation● Three Algorithm to Construct BVH
● LBVH● SAH Hierarchy Construction● Hybrid GPU Construction Algorithm
● Results & Analysis
31
Hybrid GPUConstruction Algorithm
● LBVH● Not optimized at last
● Shallow hierarchy● Large # of primitives at the leafs
● But FAST● Problem of GPU SAH Construction
● Relatively Slow● Overhead at first level● But it can build optimized hierarchy
● Solution● Top level use LBVH● Others use GPU SAH Construction
32
Contents
● What is BVH● Motivation● Three Algorithm to Construct BVH
● LBVH● SAH Hierarchy Construction● Hybrid GPU Construction Algorithm
● Results & Analysis
33
Results
● Render several scenes● Comparing with other environments
● One-core not optimized CPU SAH● Full SAH
● Standard CPU BVH ray tracer using ray packets
● Compare with● Construction time, Well Optimized, fps
34
Results
Construction TimeAbsolute/relative r.t. perf.
35
Results
Construction TimeAbsolute/relative r.t. perf.
36
Results
Construction TimeAbsolute/relative r.t. perf.
37
Results
● GPU SAH● Show better performance than CPU SAH● Good optimization
● LBVH● Fast, not optimized● Scene dependent
● Hybrid● Middle of GPU SAH & LBVH● can be customized
38
Analysis
● Current GPU architecture several features for constructing hierarchy● Special Graphics memory
significantly higher memory bandwidth● Manage fast local memory
●Discussed in Small Split Operation
● Memory● 113 bytes/triangle
●Worst case: when one triangle per leaf It allows multi-million triangle models on current GPU
39
Analysis
● Bottleneck Analysis
Core overhead
Memory overhead
40
Analysis
● Time Distribution
*Rest = read/write BVH node information,
setting up splits, join rest of steps
“Note that Hybrid build is 10 times faster”
Full SAH build Hybrid build
41
Video
● Youtube Video
42
Reference
● [SHG08] SATISH N., HARRIS M., GARLAND M.: Designing efficient sorting algorithms for manycore GPUs. Under review (2008).
● [WH06] WALD I., HAVRAN V.: On building fast kd-trees for ray tracing, and on doing that in O(N log N). In Proc. of IEEE Symp.on Interactive Ray Tracing (2006), pp. 61–69.