The goal is to reduce the affect of the fmod() used in the noise code,
which was initially reported in the comment:
https://projects.blender.org/blender/blender/pulls/119884#issuecomment-1258902
Basic idea is to benefit from SIMD vectorization on CPU.
Tested on Linux i9-11900K and macOS on M2 Ultra, in both cases performance
after this change is very close to what it could be with the fmod() commented
out (the call itself, `p = p + precision_correction`).
On macOS the penalty of fmod() was about 10%, on Linux it was closer to 30%
when built with GCC-13. With Linux builds from the buildbot it is more like 18%.
The optimization is only done for 3d and 4d noise. It might be possible to
gain some performance improvement for 1d and 2d cases, but the approach would
need to be different: we'd need to optimize scalar version fmodf(). Maybe
tricks with integer cast will be faster (since we are a bit optimistic in the
kernel and do not guarantee exact behavior in extreme cases such as NaN inputs).
Pull Request: https://projects.blender.org/blender/blender/pulls/137109
The attribute handling code in the kernel is currently highly duplicated since
it needs to handle five different data types and we couldn't use templates
back then.
We can now, so might as well make use of it and get rid of ~1000 lines.
There are also some small fixes for the GPU OSL code:
- Wrong derivative for .w component when converting float2/float3->float4
- Different conversion for float2->float (CPU averages, GPU used to take .x)
- Removed useless code for converting to float2, not used by OSL
Pull Request: https://projects.blender.org/blender/blender/pulls/134694
Check was misc-const-correctness, combined with readability-isolate-declaration
as suggested by the docs.
Temporarily clang-format "QualifierAlignment: Left" was used to get consistency
with the prevailing order of keywords.
Pull Request: https://projects.blender.org/blender/blender/pulls/132361
This is an implementation of thin film iridescence in the Principled BSDF based on "A Practical Extension to Microfacet Theory for the Modeling of Varying Iridescence".
There are still several open topics that are left for future work:
- Currently, the thin film only affects dielectric Fresnel, not metallic. Properly specifying thin films on metals requires a proper conductive Fresnel term with complex IOR inputs, any attempt of trying to hack it into the F82 model we currently use for the Principled BSDF is fundamentally flawed. In the future, we'll add a node for proper conductive Fresnel, including thin films.
- The F0/F90 control is not very elegantly implemented right now. It fundamentally works, but enabling thin film while using a Specular Tint causes a jump in appearance since the models integrate it differently. Then again, thin film interference is a physical effect, so of course a non-physical tweak doesn't play nicely with it.
- The white point handling is currently quite crude. In short: The code computes XYZ values of the reflectance spectrum, but we'd need the XYZ values of the product of the reflectance spectrum and the neutral illuminant of the working color space. Currently, this is addressed by just dividing by the XYZ values of the illuminant, but it would be better to do a proper chromatic adaptation transform or to use the proper reference curves for the working space instead of the XYZ curves from the paper.
Pull Request: https://projects.blender.org/blender/blender/pulls/118477
The Perlin noise algorithms suffer from precision issues when a coordinate
is greater than about 250000.
To fix this the Perlin noise texture is repeated every 100000 on each axis.
This causes discontinuities every 100000, however at such scales this
usually shouldn't be noticeable.
Pull Request: https://projects.blender.org/blender/blender/pulls/119884
Fractal noise is the idea of evaluating the same noise function multiple times with
different input parameters on each layer and then mixing the results. The individual
layers are usually called octaves.
The number of layers is controlled with a "Detail" slider.
The "Lacunarity" input controls a factor by which each successive layer gets scaled.
The existing Noise node already supports fractal noise. Now the Voronoi Noise node
supports it as well. The node also has a new "Normalize" property that ensures that
the output values stay in a [0.0, 1.0] range. That is except for the F2 feature where
in rare cases the output may be outside that range even with "Normalize" turned on.
How the individual octaves are mixed depends on the feature and output socket:
- F1/Smooth F1/F2:
- Distance/Color output:
The individual Distance/Color octaves are first multiplied by a factor of
`Roughness ^ (#layers - 1.0)` then added together to create the final output.
- Position output:
Each Position octave gets linearly interpolated with the combined output of the
previous octaves. The Roughness input serves as an interpolation factor with
0.0 resutling in only using the combined output of the previous octaves and
1.0 resulting in only using the current highest octave.
- Distance to Edge:
- Distance output:
The Distance octaves are mixed exactly like the Position octaves for F1/Smooth F1/F2.
It should be noted that Voronoi Noise is a relatively slow noise function, especially
at higher dimensions. Increasing the "Detail" makes it even slower. Therefore, when
optimizing a scene one should consider trying to use simpler noise functions instead
of Voronoi if the final result is close enough.
Pull Request: https://projects.blender.org/blender/blender/pulls/106827
Based on "Sampling the GGX Distribution of Visible Normals" by Eric Heitz
(https://jcgt.org/published/0007/04/01/).
Also, this removes the lambdaI computation from the Beckmann sampling code and
just recomputes it below. We already need to recompute for two other cases
(GGX and clearcoat), so this makes the code more consistent.
In terms of performance, I don't expect a notable impact since the earlier
computation also was non-trivial, and while it probably was slightly more
accurate, I'd argue that being consistent between evaluation and sampling is
more important than absolute numerical accuracy anyways.
Differential Revision: https://developer.blender.org/D17100
The distinction existed for legacy reasons, to easily port of Embree
intersection code without affecting the main vector types. However we are now
using SIMD for these types as well, so no good reason to keep the distinction.
Also more consistently pass these vector types by value in inline functions.
Previously it was partially changed for functions used by Metal to avoid having
to add address space qualifiers, simple to do it everywhere.
Also removes function declarations for vector math headers, serves no real
purpose.
Differential Revision: https://developer.blender.org/D16146
This adds support for selective rendering of caustics in shadows of refractive
objects. Example uses are rendering of underwater caustics and eye caustics.
This is based on "Manifold Next Event Estimation", a method developed for
production rendering. The idea is to selectively enable shadow caustics on a
few objects in the scene where they have a big visual impact, without impacting
render performance for the rest of the scene.
The Shadow Caustic option must be manually enabled on light, caustic receiver
and caster objects. For such light paths, the Filter Glossy option will be
ignored and replaced by sharp caustics.
Currently this method has a various limitations:
* Only caustics in shadows of refractive objects work, which means no caustics
from reflection or caustics that outside shadows. Only up to 4 refractive
caustic bounces are supported.
* Caustic caster objects should have smooth normals.
* Not currently support for Metal GPU rendering.
In the future this method may be extended for more general caustics.
TECHNICAL DETAILS
This code adds manifold next event estimation through refractive surface(s) as a
new sampling technique for direct lighting, i.e. finding the point on the
refractive surface(s) along the path to a light sample, which satisfies Fermat's
principle for a given microfacet normal and the path's end points. This
technique involves walking on the "specular manifold" using a pseudo newton
solver. Such a manifold is defined by the specular constraint matrix from the
manifold exploration framework [2]. For each refractive interface, this
constraint is defined by enforcing that the generalized half-vector projection
onto the interface local tangent plane is null. The newton solver guides the
walk by linearizing the manifold locally before reprojecting the linear solution
onto the refractive surface. See paper [1] for more details about the technique
itself and [3] for the half-vector light transport formulation, from which it is
derived.
[1] Manifold Next Event Estimation
Johannes Hanika, Marc Droske, and Luca Fascione. 2015.
Comput. Graph. Forum 34, 4 (July 2015), 87–97.
https://jo.dreggn.org/home/2015_mnee.pdf
[2] Manifold exploration: a Markov Chain Monte Carlo technique for rendering
scenes with difficult specular transport Wenzel Jakob and Steve Marschner.
2012. ACM Trans. Graph. 31, 4, Article 58 (July 2012), 13 pages.
https://www.cs.cornell.edu/projects/manifolds-sg12/
[3] The Natural-Constraint Representation of the Path Space for Efficient
Light Transport Simulation. Anton S. Kaplanyan, Johannes Hanika, and Carsten
Dachsbacher. 2014. ACM Trans. Graph. 33, 4, Article 102 (July 2014), 13 pages.
https://cg.ivd.kit.edu/english/HSLT.php
The code for this samping technique was inserted at the light sampling stage
(direct lighting). If the walk is successful, it turns off path regularization
using a specialized flag in the path state (PATH_MNEE_SUCCESS). This flag tells
the integrator not to blur the brdf roughness further down the path (in a child
ray created from BSDF sampling). In addition, using a cascading mechanism of
flag values, we cull connections to caustic lights for this and children rays,
which should be resolved through MNEE.
This mechanism also cancels the MIS bsdf counter part at the casutic receiver
depth, in essence leaving MNEE as the only sampling technique from receivers
through refractive casters to caustic lights. This choice might not be optimal
when the light gets large wrt to the receiver, though this is usually not when
you want to use MNEE.
This connection culling strategy removes a fair amount of fireflies, at the cost
of introducing a slight bias. Because of the selective nature of the culling
mechanism, reflective caustics still benefit from the native path
regularization, which further removes fireflies on other surfaces (bouncing
light off casters).
Differential Revision: https://developer.blender.org/D13533
* Replace license text in headers with SPDX identifiers.
* Remove specific license info from outdated readme.txt, instead leave details
to the source files.
* Add list of SPDX license identifiers used, and corresponding license texts.
* Update copyright dates while we're at it.
Ref D14069, T95597
This patch contains many small leftover fixes and additions that are
required for Metal-enablement:
- Address space fixes and a few other small compile fixes
- Addition of missing functionality to the Metal adapter headers
- Addition of various scattered `__KERNEL_METAL__` blocks (e.g. for
atomic support & maths functions)
Ref T92212
Differential Revision: https://developer.blender.org/D13263
Remove prefix of filenames that is the same as the folder name. This used
to help when #includes were using individual files, but now they are always
relative to the cycles root directory and so the prefixes are redundant.
For patches and branches, git merge and rebase should be able to detect the
renames and move over code to the right file.
