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@@ -1,3 +1,107 @@
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Tue May 6 07:21:09 UTC 2025 - Guillaume GARDET <guillaume.gardet@opensuse.org>
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- Enable build on aarch64
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-------------------------------------------------------------------
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Sat Apr 5 21:34:02 UTC 2025 - Marcus Rueckert <mrueckert@suse.de>
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- Update to 2.3.3:
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- Added NVIDIA Blackwell GPU support
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- Added AMD RDNA4 GPU support
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- Improved performance for AMD RDNA3 GPUs
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- Added OIDN_DEPENDENTLOADFLAG CMake option for setting the
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DEPENDENTLOADFLAG linker flag on Windows
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- Added OIDN_LIBRARY_VERSIONED CMake option for toggling
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versioning in the Open Image Denoise library files
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- Known issue: performance regression for AMD RDNA2 GPUs
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-------------------------------------------------------------------
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Sat Apr 5 21:33:34 UTC 2025 - Marcus Rueckert <mrueckert@suse.de>
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- Update to 2.3.2:
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- Improved performance for Intel Lunar Lake and Battlemage GPUs
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- Added Intel Panther Lake GPU support
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- Fixed compile error when building with OpenImageIO 3.x
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-------------------------------------------------------------------
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Sat Apr 5 21:32:16 UTC 2025 - Marcus Rueckert <mrueckert@suse.de>
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- Update to 2.3.1:
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- Fixed corrupted output when in-place denoising high-resolution
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(> 1080p) images where the input and output are stored in
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different shared buffer objects (created with
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oidnNewSharedBuffer*) that overlap in memory
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- Fixed issues with cancellation through progress monitor
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callbacks:
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- Fixed cancellation requests not being fulfilled on CPU
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devices since v2.3.0
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- Fixed not calling the callback anymore after requesting
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cancellation, while the operation is still being executed
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- Added support for creating shared buffers on Metal devices
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- Enabled accessing system allocated memory for CUDA devices
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which support this feature (see systemMemorySupported device
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parameter)
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- Added LUID support for HIP devices. Importing DX12 and Vulkan
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buffers is now functional when using recent AMD GPU drivers on
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Windows
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-------------------------------------------------------------------
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Sat Apr 5 21:27:27 UTC 2025 - Marcus Rueckert <mrueckert@suse.de>
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- Update to 2.3.0:
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- Significantly improved image quality of the RT filter in high
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quality mode for HDR denoising with prefiltering, i.e., the
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following combinations of input features and parameters:
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- HDR color + albedo + normal + cleanAux
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- albedo
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- normal
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In these cases a much more complex filter is used, which
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results in lower performance than before (about 2x). To revert
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to the previous performance behavior, please switch to the
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balanced quality mode.
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- Added fast quality mode (OIDN_QUALITY_FAST) for even higher
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performance (about 1.5-2x) interactive/real-time previews and
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lower default memory usage at the cost of somewhat lower image
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quality. Currently this is implemented for the RT filter except
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prefiltering (albedo, normal). In other cases denoising
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implicitly falls back to balanced mode.
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- Added Intel Arrow Lake, Lunar Lake, and Battlemage GPU support
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- Execute Async functions asynchronously on CPU devices as well
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- Load/initialize device modules lazily (improves stability)
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- Added oidnIsCPUDeviceSupported, oidnIsSYCLDeviceSupported,
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oidnIsCUDADeviceSupported, oidnIsHIPDeviceSupported, and
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oidnIsMetalDeviceSupported API functions for checking whether a
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physical device of a particular type is supported
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- Release the CUDA primary context when destroying the device
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object if using the CUDA driver API
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- Added OIDN_LIBRARY_NAME CMake option for setting the base name
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of the Open Image Denoise library files
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- Fixed device creation error with oidnNewDevice when the default
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device of the specified type (e.g. CUDA) is not supported but
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there are other supported non-default devices of that type in
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the system
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- Fixed CMake error when building with Metal support using
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non-Apple Clang
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- Fixed iOS build errors
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- Added support for building with ROCm 6.x oidnNewCUDADevice and
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oidnNewHIPDevice no longer accept negative device IDs. If the
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goal is to use the current device, its actual ID needs to be
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passed.
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- Upgraded to oneTBB 2021.12.0 in the official binaries
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- Training:
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- Improved training performance on CUDA and MPS devices, added
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--compile option
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- Added --quality option (high, balanced, fast) for selecting
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the size of the model to train, changed the default from
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balanced to high
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- Added new models to the --model option (unet_small,
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unet_large, unet_xl)
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- Added support for training with prefiltered auxiliary
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features by passing --aux_results to preprocess.py and
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train.py
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- Added experimental support for depth (z)
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-------------------------------------------------------------------
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Tue Apr 30 20:52:47 UTC 2024 - Marcus Rueckert <mrueckert@suse.de>
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