ZenDNN library, which includes APIs for basic neural network building blocks optimized for AMD CPU architecture, targets deep learning application and framework developers with the goal of improving deep learning inference performance on AMD CPUs.
For the current version, refer to the ZenDNN page.
ZenDNN v3.2 Highlights
- Enabled, tuned, and optimized for AMD 2nd and 3rd Gen EPYCTM processors
- Integrated with TensorFlow v2.7, PyTorch v1.9.0, and ONNXRT v1.8.0
- Features highly optimized primitives for AMD CPUs, targeting a variety of workloads, including computer vision, natural language processing, and recommender systems
- Tested with a variety of neural network models across three major workload types:
- Computer Vision: AlexNet, InceptionV3, InceptionV4, GoogLeNet, ResNet50, ResNet152, VGG16, and VGG19
- Natural Language Processing: BERT
- Recommender Systems: DLRM, Wide & Deep
- Supported on Ubuntu 18.04, Ubuntu 20.04, RHEL 8.3, and CentOS 8.3
|3.2||TensorFlow v2.7, PyTorch v1.9.0, and ONNXRT v1.8.0
||Ubuntu 18.04, Ubuntu 19.10, Ubuntu 20.04, RHEL 8.3, and CentOS 8.3||ZenDNN 3.2 – Documents|
|3.1||TensorFlow v2.5||Ubuntu 18.04, Ubuntu 19.10, Ubuntu 20.04, RHEL 8.3, and CentOS 8.3||ZenDNN 3.1 – Documents|
|3.0||TensorFlow v1.15 and ONNXRT v1.5.1||Ubuntu 18.04, Ubuntu 19.10, Ubuntu 20.04, RHEL 8.3, and CentOS 8.3||ZenDNN 3.0 – Documents|