Open Image Denoise v2.3.3

• Added NVIDIA Blackwell GPU support
• Added AMD RDNA4 GPU support
• Improved performance for AMD RDNA3 GPUs
• Added OIDN_DEPENDENTLOADFLAG CMake option for setting the DEPENDENTLOADFLAG linker flag on Windows
• Added OIDN_LIBRARY_VERSIONED CMake option for toggling versioning in the Open Image Denoise library files
• Known issue: performance regression for AMD RDNA2 GPUs

Open Image Denoise v2.3.2

• Improved performance for Intel Lunar Lake and Battlemage GPUs
• Added Intel Panther Lake GPU support
• Fixed compile error when building with OpenImageIO 3.x

Open Image Denoise v2.3.1

• Fixed corrupted output when in-place denoising high-resolution (> 1080p)
  images where the input and output are stored in different shared buffer
  objects (created with oidnNewSharedBuffer*) that overlap in memory
• Fixed issues with cancellation through progress monitor callbacks:
  • Fixed cancellation requests not being fulfilled on CPU devices since
    v2.3.0
  • Fixed not calling the callback anymore after requesting cancellation,
    while the operation is still being executed
• Added support for creating shared buffers on Metal devices
• Enabled accessing system allocated memory for CUDA devices which support this
  feature (see systemMemorySupported device parameter)
• Added LUID support for HIP devices. Importing DX12 and Vulkan buffers is
  now functional when using recent AMD GPU drivers on Windows

Open Image Denoise v2.3.0

• Significantly improved image quality of the RT filter in high quality
  mode for HDR denoising with prefiltering, i.e., the following combinations
  of input features and parameters:
  - HDR color + albedo + normal + cleanAux
  - albedo
  - normal
  In these cases a much more complex filter is used, which results in lower
  performance than before (about 2x). To revert to the previous performance
  behavior, please switch to the balanced quality mode.
• Added fast quality mode (OIDN_QUALITY_FAST) for even higher performance
  (about 1.5-2x) interactive/real-time previews and lower default memory usage
  at the cost of somewhat lower image quality. Currently this is implemented
  for the RT filter except prefiltering (albedo, normal). In other cases
  denoising implicitly falls back to balanced mode.
• Added Intel Arrow Lake, Lunar Lake, and Battlemage GPU support
• Execute Async functions asynchronously on CPU devices as well
• Load/initialize device modules lazily (improves stability)
• Added oidnIsCPUDeviceSupported, oidnIsSYCLDeviceSupported,
  oidnIsCUDADeviceSupported, oidnIsHIPDeviceSupported,
  and oidnIsMetalDeviceSupported API functions for checking whether a
  physical device of a particular type is supported
• Release the CUDA primary context when destroying the device object if using
  the CUDA driver API
• Added OIDN_LIBRARY_NAME CMake option for setting the base name of the Open
  Image Denoise library files
• Fixed device creation error with oidnNewDevice when the default device of
  the specified type (e.g. CUDA) is not supported but there are other
  supported non-default devices of that type in the system
• Fixed CMake error when building with Metal support using non-Apple Clang
• Fixed iOS build errors
• Added support for building with ROCm 6.x
• oidnNewCUDADevice and oidnNewHIPDevice no longer accept negative device
  IDs. If the goal is to use the current device, its actual ID needs to be
  passed.
• Upgraded to oneTBB 2021.12.0 in the official binaries
• Training:
  • Improved training performance on CUDA and MPS devices, added --compile
    option
  • Added --quality option (high, balanced, fast) for selecting the
    size of the model to train, changed the default from balanced to high
  • Added new models to the --model option (unet_small, unet_large,
    unet_xl)
  • Added support for training with prefiltered auxiliary features by
    passing --aux_results to preprocess.py and train.py
  • Added experimental support for depth (z)

Open Image Denoise v2.3.0-beta

• Significantly improved image quality of the RT filter in high quality
  mode for HDR denoising with prefiltering, i.e., the following combinations
  of input features and parameters:
  - HDR color + albedo + normal + cleanAux
  - albedo
  - normal
  In these cases a much more complex filter is used, which results in lower
  performance than before (about 2x). To revert to the previous performance
  behavior, please switch to the balanced quality mode.
• Added fast quality mode (OIDN_QUALITY_FAST) for even higher performance
  (about 1.5-2x) interactive/real-time previews and lower default memory usage
  at the cost of somewhat lower image quality. Currently this is implemented
  for the RT filter except prefiltering (albedo, normal). In other cases
  denoising implicitly falls back to balanced mode.
• Execute Async functions asynchronously on CPU devices as well
• Load/initialize device modules lazily (improves stability)
• Added oidnIsCPUDeviceSupported, oidnIsSYCLDeviceSupported,
  oidnIsCUDADeviceSupported, oidnIsHIPDeviceSupported,
  and oidnIsMetalDeviceSupported API functions for checking whether a
  physical device of a particular type is supported
• Release the CUDA primary context when destroying the device object if using
  the CUDA driver API
• Fixed device creation error with oidnNewDevice when the default device of
  the specified type (e.g. CUDA) is not supported but there are other
  supported non-default devices of that type in the system
• Added support for building with ROCm 6.x
• oidnNewCUDADevice and oidnNewHIPDevice no longer accept negative device
  IDs. If the goal is to use the current device, its actual ID needs to be
  passed.
• Upgraded to oneTBB 2021.12.0 in the official binaries

Open Image Denoise v2.2.2

• Fully fixed GPU memory leak when releasing SYCL, CUDA and HIP device objects
• Fixed CUDA context error in some cases when using the CUDA driver API
• Fixed crash on systems with an unsupported AMD Vega integrated GPU and old
  driver

Open Image Denoise v2.2.1

• Fixed memory leak when releasing SYCL, CUDA and HIP device objects
• Fixed memory leak when initializing Metal filters

Open Image Denoise v2.2.0

• Improved denoising quality (better fine detail reconstruction)
• Added Intel Meteor Lake GPU support (in Intel® Core™ Ultra Processors)
• Added Metal device for Apple silicon GPUs (requires macOS Ventura or newer)
• Added ARM64 (AArch64) CPU support on Windows and Linux (in addition to macOS)
• Improved CPU performance
• Significantly reduced overhead of committing filter changes
• Switched to the CUDA driver API by default, added the OIDN_DEVICE_CUDA_API
  CMake option for manually selecting between the driver and runtime APIs
• Fixed crash when releasing a buffer after releasing the device

Open Image Denoise v2.2.0-rc2

• Improved denoising quality (better fine detail reconstruction)
• Added Intel Meteor Lake GPU support (in Intel® Core™ Ultra Processors)
• Added Metal device for Apple silicon GPUs (requires macOS Ventura or newer)
• Added ARM64 (AArch64) CPU support on Windows and Linux (in addition to macOS)
• Improved CPU performance
• Switched to the CUDA driver API by default, added the OIDN_DEVICE_CUDA_API
  CMake option for manually selecting between the driver and runtime APIs
• Fixed crash when releasing a buffer after releasing the device

Open Image Denoise v2.2.0-rc

• Improved denoising quality (better fine detail reconstruction)
• Added Intel Meteor Lake GPU support (in Intel® Core™ Ultra Processors)
• Added Metal device for Apple silicon GPUs (requires macOS Ventura or newer)
• Added ARM64 (AArch64) CPU support on Windows and Linux (in addition to macOS)
• Improved CPU performance
• Switched to the CUDA driver API by default, added the OIDN_DEVICE_CUDA_API
  CMake option for manually selecting between the driver and runtime APIs
• Fixed crash when releasing a buffer after releasing the device