This reverts commit 3f31c28a02.
Gives issues zooming, could be resolved but it mostly worked OK before,
and it's not a priority to spend time on, so leave as is for now.
Now used the original dist instead, since using the distance between
the camera and the views offset may seem random from the users POV.
This addresses strange behavior noticed in T56934.
The idea is to make main thread and job threads to be scheduled
on CPU dies which has direct access to memory (those are NUMA
nodes 0 and 2).
We also do this for new EPYC CPUs since their NUMA nodes 1 and 3
do have access but only to a higher range DDR slots. By preferring
nodes 0 and 2 on EPYC we make it so users with partially filled
DDR slots has fast memory access.
One thing which is not really solved yet is localization of
memory allocation: we do not guarantee that memory is allocated
on the closest to the NUMA node DDR slot and hope that memory
manager of OS is acting in favor of us.
Second part of the fix: do not try at all to compute normals in degenerated
geometry. Just loss of time and potential issues later with weird
invalid computed values.
The goal is to address performance regression when going from
few threads to 10s of threads. On a systems with more than 32
CPU threads the benefit of threaded loop was actually harmful.
There are following tweaks now:
- The chunk size is adaptive for the number of threads, which
minimizes scheduling overhead.
- The number of tasks is adaptive to the list size and chunk
size.
Here comes performance comparison on the production shot:
Number of threads DEG time before DEG time after
44 0.09 0.02
32 0.055 0.025
16 0.025 0.025
8 0.035 0.033
Note that this is turned off by default and must be enabled at build time with the CMake WITH_CYCLES_EMBREE flag.
Embree must be built as a static library with ray masking turned on, the `make deps` scripts have been updated accordingly.
There, Embree is off by default too and must be enabled with the WITH_EMBREE flag.
Using Embree allows for much faster rendering of deformation motion blur while reducing the memory footprint.
TODO: GPU implementation, deduplication of data, leveraging more of Embrees features (e.g. tessellation cache).
Differential Revision: https://developer.blender.org/D3682
