AccelerateRT
Explore acceleration structures (BVHs) for ray tracing.
Final project for Duke University CS634: Geometric Algorithms.
Project Setup
First make sure you have Julia language installed.
Then install project dependencies locally from command line:
>> julia
_
_ _ _(_)_ | Documentation: https://docs.julialang.org
(_) | (_) (_) |
_ _ _| |_ __ _ | Type "?" for help, "]?" for Pkg help.
| | | | | | |/ _` | |
| | |_| | | | (_| | | Version 1.7.0 (2021-11-30)
_/ |\__'_|_|_|\__'_| | Official https://julialang.org/ release
|__/ |
julia> ]
(@v1.7) pkg> activate .
(AccelerateRT) pkg> instantiate
julia> exit()
BVH Construction
Commands
>> julia .\construct.jl -h
usage: construct.jl [--algMiddle] [--algMedian] [--algSAH] [--algSAHM]
[--save] [--skip] [--show] [-h] model
positional arguments:
model obj model path
optional arguments:
--algMiddle construct simple BVH with middle criteria
--algMedian construct simple BVH with media criteria
--algSAH construct BVH with SAH
--algSAHM construct BVH with modifed SAH (new algorithm)
--save save constructed structure
--skip skip existing structure
--show print structure
-h, --help show this help message and exit
For example, following command constructs simple BVH with median criteria for bunny model.
Saving the computed structure at the end into structures folder.
>> julia .\construct.jl .\models\bunny\bunny.obj --algMedian --save
Visualization
Commands
>> julia .\visualize.jl -h
usage: visualize.jl [--bvh BVH] [-h] model
positional arguments:
model obj model path
optional arguments:
--bvh BVH constructed BVH path
-h, --help show this help message and exit
For example, following command visualizes teapot model in an interactive environment.
>> julia .\visualize.jl .\models\teapot\teapot.obj
The following command visualizes bunny model and its precomputed BVH structure.
>> julia .\visualize.jl .\models\bunny\bunny.obj --bvh .\structures\__models_bunny_bunny_obj.median.jld2
Benchmark
Commands
>> julia .\benchmark.jl -h
usage: benchmark.jl [--seed SEED] [--samples SAMPLES]
[--resolution RESOLUTION] [--skip] [--time] [-h]
optional arguments:
--seed SEED random seed (type: Int64, default: 0)
--samples SAMPLES number of random samples (type: Int64,
default: 100)
--resolution RESOLUTION
screen resolution (in format WxH) (default:
"50x50")
--skip whether to skip existing benchmark caches
--time display time after all tasks done
-h, --help show this help message and exit
For example, the following executes benchmark with 4 threads available for each worker, 200 random samples for each configuration, and random seed set to 123, and display time info after all tasks done:
>> julia -t 4 .\benchmark.jl --samples 200 --seed 123 --time
By default, benchmark.jl distributes workers to all cores available. Modify ParallelCores variable to change this behavior: 0 for all cores, 1 for single-process, else customized number of workers.
More info can be found in benchmark_notebook.jl notebook, or by opening benchmark_notebook.jl.pdf file.
To execute it:
>> julia
julia> import Pluto
julia> Pluto.run()
And open benchmark_notebook.jl in browser.
To see the code only, open benchmark_notebook.jl in a text editor.