Experimental feature set id currently unavailable for megakernel, it'll
require some changes to the cache system to distinguish cached regular
kernels from cached experimental kernels.
Currently unused, but some features will be enabled soon.
This required allocating some memory related on object transform needed
by ShaderData and currently it is done for all the platforms. Since we're
targeting full feature-complete platforms this is rather acceptable at
this point and in the future we'll do selective NO_HAIR/NO_SSS/NO_BLUR
kernels.
This is experimental still and in fact there're some major issues on
NVidia platform and it's not really clear if it's a bug in compiler,
some uninitizlied variable or other kind of issue.
Some stupid fixes like spaces around operator and missing semicolon,
plus fix for wrong detecting of ShaderData SOA size. Thar was harmless
since there's only one closure array, but still better to fix this.
This file was actually checking for features enabled on CPU and surely all
of them were enabled, so removing them does not cause any difference.
ideally we'll need to do runtime feature detection and just pass some stuff
as NULL to the kernel, or maybe also have variadic kernel entry points which
is also possible quite easily.
No need to store them in the class, they're unlikely to be changed
and if they do change we're in big trouble anyway.
More appropriate approach would be then to typedef this things in
kernel_types.h, but still use inlined sizeof(),
Only those ones are priority for now, all the rest are still testable
if CYCLES_OPENCL_TEST or CYCLES_OPENCL_SPLIT_KERNEL_TEST environment
variables are set.
This commit contains all the work related on the AMD megakernel split work
which was mainly done by Varun Sundar, George Kyriazis and Lenny Wang, plus
some help from Sergey Sharybin, Martijn Berger, Thomas Dinges and likely
someone else which we're forgetting to mention.
Currently only AMD cards are enabled for the new split kernel, but it is
possible to force split opencl kernel to be used by setting the following
environment variable: CYCLES_OPENCL_SPLIT_KERNEL_TEST=1.
Not all the features are supported yet, and that being said no motion blur,
camera blur, SSS and volumetrics for now. Also transparent shadows are
disabled on AMD device because of some compiler bug.
This kernel is also only implements regular path tracing and supporting
branched one will take a bit. Branched path tracing is exposed to the
interface still, which is a bit misleading and will be hidden there soon.
More feature will be enabled once they're ported to the split kernel and
tested.
Neither regular CPU nor CUDA has any difference, they're generating the
same exact code, which means no regressions/improvements there.
Based on the research paper:
https://research.nvidia.com/sites/default/files/publications/laine2013hpg_paper.pdf
Here's the documentation:
https://docs.google.com/document/d/1LuXW-CV-sVJkQaEGZlMJ86jZ8FmoPfecaMdR-oiWbUY/edit
Design discussion of the patch:
https://developer.blender.org/T44197
Differential Revision: https://developer.blender.org/D1200
This is currently unused but crucial for things like calculating amount of
device memory required to deal with the tasks.
Maybe not really best place to store it, but consider it good enough for now.
Previously we only had experimental flag passed to device's load_kernel() which
was all fine. But since we're gonna to have some extra parameters passed there
it makes sense to wrap them into a single struct, which will make it easier to
pass stuff around.
This inconsistency drove me totally crazy, it's really confusing
when it's inconsistent especially when you work on both Cycles and
Blender sides.
Shouldn;t cause merge PITA, it's whitespace changes only, Git should
be able to merge it nicely.
For CPU it gives available instructions set (SSE, AVX and so).
For GPU CUDA it reports most of the attribute values returned by
cuDeviceGetAttribute(). Ideally we need to only use set of those
which are driver-specific (so we don't clutter system info with
values which we can get from GPU specifications and be sure they
stay the same because driver can't affect on them).
This is what was handy troubleshooting issues in the studio,
plus this is exactly the same thing which would be helpful
when solving issues with paths to compiled shaders and cubins
for standalone repository.
Single precision exponent on 64bit linux tends to be order of magnitude slower
than double precision version even with single<->double precision conversion.
Some feedback in the mailing lists also suggests that logf() is also slow, but
this i didn't confirm here in the studio yet.
Depending on the shader setup it gives ~3% with the secret agent shot and up to
around 15% with the bmw scene here.
Quite straightforward change, the only annoying thing is that we can't use
indentation for include directive just because of the way headers inlineing
works for OpenCL.
Might do smarter job in path_source_replace_includes() but don't want to
spend time on this yet.
This adds an AABB collision check for objects with volumes and if there's a
collision detected then the object will have SD_OBJECT_INTERSECTS_VOLUME flag.
This solves a speed regression introduced by the fix for T39823 by skipping
volume stack update in cases no volumes intersects the current SSS object.
This is rather legit case which happens i.e. when having persistent images enabled
and session is updating the lookup tables.
Now device_memory keeps track of amount of memory being allocated on the device,
which makes freeing using the proper allocated size, not the CPU side buffer
size.
Now we build 2 .cubins per architecture (e.g. kernel_sm_21.cubin, kernel_experimental_sm_21.cubin).
The experimental kernel can be used by switching to the Experimental Feature Set: http://wiki.blender.org/index.php/Doc:2.6/Manual/Render/Cycles/Experimental_Features
This enables Subsurface Scattering and Correlated Multi Jitter Sampling on GPU, while keeping the stability and performance of the regular kernel.
Differential Revision: https://developer.blender.org/D762
Patch by Sergey and myself.
Developer / Builder Note:
CUDA Toolkit 6.5 is highly recommended for this, also note that building the experimental kernel requires a lot of system memory (~7-8GB).
This problem was introduced in 983cbafd18
Basically the issue is that we were not getting a unique index in the
baking routine for the RNG (random number generator).
Reviewers: sergey
Differential Revision: https://developer.blender.org/D749
