Octane X accelerates modern creative workflows with ACES, OCIO and deep pixel EXR rendering, a powerful node-based material, shader and scene graph editor, and the industry’s most advanced production ready AI Denoiser. This exclusive version of Octane X for the App Store features multi-GPU rendering, network rendering (through an additional Octane Enterprise Render Node license) and Apple M1 native GPU rendering support. Octane X is optimized for maximum rendering performance on AMD Polaris, Vega and Navi GPUs as well as Intel SkyLake GPUs on macOS Big Sur 11.1 and later. Some introductory material is available on our forum:
Support for Windows and Linux with the latest NVIDIA data center and mobile GPUs.Octane X is the world’s first and fastest unbiased, spectrally-correct GPU production renderer for macOS, built from the ground up for maximum performance on Apple Metal and Apple Silicon, and empowering artist workflows across visual effects, motion graphics, gaming, design, concept art and architectural visualization.Support for fusion of memory-limited operations like pointwise and reduction with math-limited operations like convolution and matmul.Support for FP32, FP16, BF16 and TF32 floating point formats and INT8, and UINT8 integer formats.Optimized kernels for computer vision and speech models including ResNet, ResNext, EfficientNet, EfficientDet, SSD, MaskRCNN, Unet, VNet, BERT, GPT-2, Tacotron2 and WaveGlow.Tensor Core acceleration for all popular convolutions including 2D, 3D, Grouped, Depth-wise separable, and Dilated with NHWC and NCHW inputs and outputs.For access to NVIDIA optimized deep learning framework containers that have cuDNN integrated into frameworks, visit NVIDIA GPU CLOUD to learn more and get started.ĭownload cuDNN Developer Guide Forums Latest Release Notes cuDNN accelerates widely used deep learning frameworks, including Caffe2, Chainer, Keras, MATLAB, MxNet, PaddlePaddle, PyTorch, and TensorFlow. 'Cycles will render on the CPU' (2.80rc3) Im never able to use it for more than 1 minute.
It allows them to focus on training neural networks and developing software applications rather than spending time on low-level GPU performance tuning. This is the highest spec you can buy today in a MacBook Pro. cuDNN provides highly tuned implementations for standard routines such as forward and backward convolution, pooling, normalization, and activation layers.ĭeep learning researchers and framework developers worldwide rely on cuDNN for high-performance GPU acceleration. The NVIDIA CUDA® Deep Neural Network library (cuDNN) is a GPU-accelerated library of primitives for deep neural networks.
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