NEW! ZenDNN 1.5R is now available
ZenDNN (Zen Deep Neural Network) Library accelerates deep learning inference applications on AMD CPUs. This library, which includes APIs for basic neural network building blocks optimized for AMD Processors, targets deep learning applications and framework developers with the goal of improving inference application performance on AMD CPUs.
- Target released for AMD EPYCTM processor family.
- Contains ZenDNN Binary, TF wheel file (*.whl), End User License Agreement, ZenDNN User Guide
- Integrated with TensorFlow 1.15
- Features highly optimized primitives, including: Convolution, MatMul, Elementwise (Binary), BatchNorm, and ReLU for AMD CPUs
- Tested with the following models: AlexNet, InceptionV3, InceptionV4, GoogLeNet, ResNet50, ResNet152, VGG16, VGG19, BERT, DLRM, Wide & Deep
- Tested on Ubuntu 18.04, Ubuntu 19.10, Ubuntu 20.04, RHEL 8.2
Resources and Technical Support
The demo below compares SSDLite Mobilenet V2 inference performance using ZenDNN TF and vanilla TF on AMD EPYC 7742. For this object detection workload, about 53% improvement using ZenDNN TF over vanilla TF was observed.
ZenDNN is a well-supported library. Technical support is available to all customers via the channel below:
- Email based support: To access 1×1 support, report issues, or request expert help, please email email@example.com.