Commit Graph

19 Commits

Author SHA1 Message Date
Patrick Mours
a9644c812f Cycles: Use pre-compiled PTX kernel for older generation when no matching one is found
This patch changes the discovery of pre-compiled kernels, to look for any PTX, even if
it does not match the current architecture version exactly. It works because the driver can
JIT-compile PTX generated for architectures less than or equal to the current one.
This e.g. makes it possible to render on a new GPU architecture even if no pre-compiled
binary kernel was distributed for it as part of the Blender installation.

Reviewed By: brecht

Differential Revision: https://developer.blender.org/D8332
2020-07-20 19:25:27 +02:00
Brecht Van Lommel
93791381fe Cleanup: reduce hardcoded numbers in denoising neighbor tiles code 2020-07-10 17:10:05 +02:00
Brecht Van Lommel
54e3487c9e Cleanup: remove task pool stop() and finished() 2020-06-22 13:06:47 +02:00
Brecht Van Lommel
b10b7cdb43 Cleanup: use lambdas instead of functors for task pools, remove threadid 2020-06-22 13:06:47 +02:00
Brecht Van Lommel
ace3268482 Cleanup: minor refactoring around DeviceTask 2020-06-22 13:06:47 +02:00
Patrick Mours
b586f801fc Cycles: Improve CUDA and OptiX error reporting in the viewport
This patch makes the infamous "Cancel" error in the viewport a thing of the past. Instead it
now shows a more useful error message and streamlines the error handling process in CUDA.

Reviewed By: brecht

Differential Revision: https://developer.blender.org/D8008
2020-06-12 18:24:15 +02:00
Patrick Mours
9f7d84b656 Cycles: Add support for P2P memory distribution (e.g. via NVLink)
This change modifies the multi-device implementation to support memory distribution
across devices, to reduce the overall memory footprint of large scenes and allow scenes to
fit entirely into combined GPU memory that previously had to fall back to host memory.

Reviewed By: brecht

Differential Revision: https://developer.blender.org/D7426
2020-06-08 17:55:49 +02:00
Brecht Van Lommel
d9773edaa3 Cycles: code refactor to bake using regular render session and tiles
There should be no user visible change from this, except that tile size
now affects performance. The goal here is to simplify bake denoising in
D3099, letting it reuse more denoising tiles and pass code.

A lot of code is now shared with regular rendering, with the two main
differences being that we read some render result passes from the bake API
when starting to render a tile, and call the bake kernel instead of the
path trace kernel.

With this kind of design where Cycles asks for tiles from the bake API,
it should eventually be easier to reduce memory usage, show tiles as
they are baked, or bake multiple passes at once, though there's still
quite some work needed for that.

Reviewers: #cycles

Subscribers: monio, wmatyjewicz, lukasstockner97, michaelknubben

Differential Revision: https://developer.blender.org/D3108
2020-05-15 20:25:24 +02:00
Brecht Van Lommel
d97c83712c Cycles: mark CUDA 10.2 as officially supported
It appears to work fine after a recent bugfix and testing for the past few
weeks.
2020-05-05 15:06:49 +02:00
Dalai Felinto
2d1cce8331 Cleanup: make format after SortedIncludes change 2020-03-19 09:33:58 +01:00
Brecht Van Lommel
26bea849cf Cleanup: add device_texture for images, distinct from other global memory
There was too much image texture specific stuff in device_memory, and too
much code duplication between devices.
2020-03-12 17:28:55 +01:00
Brecht Van Lommel
f01bc597a8 Cleanup: stop encoding image data type in slot index
This is legacy code from when we had a fixed number of textures.
2020-03-11 17:07:17 +01:00
Campbell Barton
8574d68aa0 Cleanup: spelling 2020-03-06 11:52:32 +11:00
Stefan Werner
51e898324d Adaptive Sampling for Cycles.
This feature takes some inspiration from
"RenderMan: An Advanced Path Tracing Architecture for Movie Rendering" and
"A Hierarchical Automatic Stopping Condition for Monte Carlo Global Illumination"

The basic principle is as follows:
While samples are being added to a pixel, the adaptive sampler writes half
of the samples to a separate buffer. This gives it two separate estimates
of the same pixel, and by comparing their difference it estimates convergence.
Once convergence drops below a given threshold, the pixel is considered done.

When a pixel has not converged yet and needs more samples than the minimum,
its immediate neighbors are also set to take more samples. This is done in order
to more reliably detect sharp features such as caustics. A 3x3 box filter that
is run periodically over the tile buffer is used for that purpose.

After a tile has finished rendering, the values of all passes are scaled as if
they were rendered with the full number of samples. This way, any code operating
on these buffers, for example the denoiser, does not need to be changed for
per-pixel sample counts.

Reviewed By: brecht, #cycles

Differential Revision: https://developer.blender.org/D4686
2020-03-05 12:21:38 +01:00
Patrick Mours
af54bbd61c Cycles: Rework tile scheduling for denoising
This fixes denoising being delayed until after all rendering has finished. Instead, tile-based
denoising is now part of the "RENDER" task again, so that it is all in one task and does not
cause issues with dedicated task pools where tasks are serialized.

Reviewed By: brecht

Differential Revision: https://developer.blender.org/D6940
2020-02-28 16:12:29 +01:00
Patrick Mours
a93043153a Cleanup: Remove superfluous "cuda_device_ptr" function 2020-02-25 17:13:59 +01:00
Dalai Felinto
213b4f76ee Cleanup: make format 2020-02-19 18:44:22 +01:00
Patrick Mours
2278aa0da9 Cycles: Add support for adaptive kernel compilation to OptiX device
This modifies the common CUDA implementation for adaptive kernel compilation slightly to support both CUBIN and PTX output (the latter which is then used in the OptiX device). It also fixes adaptive kernel compilation on Windows.

Reviewed By: brecht

Differential Revision: https://developer.blender.org/D6851
2020-02-17 14:27:44 +01:00
Patrick Mours
153e001c74 Cleanup: Move common CUDA/OptiX Cycles device code into separate file
This reduces code duplication between the CUDA and OptiX device implementations: The CUDA device
class is now split into declaration and definition (similar to the OpenCL device) and the OptiX device
class implements that and only overrides the functions it actually has to change, while using the CUDA
implementation for everything else.

Reviewed By: brecht

Differential Revision: https://developer.blender.org/D6814
2020-02-12 13:11:32 +01:00