https://github.com/amd/zendnn-tensorflow-plugin - zentf Release v5.0.2

zentf 5.0.2 is the TensorFlow plugin which comes with ZenDNN 5.0.2, which is a minor release building upon the major ZenDNN 5.0 release. This upgrade continues the focus on optimizing inference with Recommender Systems and Large Language Models on AMD EPYC™ CPUs.

zentf 5.0.2 includes enhancements for bfloat16 performance, primarily by leveraging microkernels and operators from the ZenDNN 5.0.2 library. These operators are designed to better leverage the EPYC microarchitecture and cache hierarchy. The zentf 5.0.2 plugin works seamlessly with TensorFlow versions from the latest 2.18 to 2.16, offering a high-performance experience for deep learning on AMD EPYC™ platforms.

This release adds support for Java interfaces through TensorFlow Java v1.0.0

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Published by kiriti-pendyala 11 months ago

https://github.com/amd/zendnn-tensorflow-plugin - zentf Release v5.0.1

zentf 5.0.1 is the TensorFlow plugin which comes with ZenDNN 5.0.1, which is a minor release building upon the major ZenDNN 5.0 release. This upgrade continues the focus on optimizing inference with Recommender Systems and Large Language Models on AMD EPYC™ CPUs.

zentf 5.0.1 includes enhancements for bfloat16 performance, primarily by leveraging microkernels and operators from the ZenDNN 5.0.1 library. These operators are designed to better leverage the EPYC microarchitecture and cache hierarchy.

The zentf 5.0.1 plugin works seamlessly with TensorFlow versions from the latest 2.18 to 2.16, offering a high-performance experience for deep learning on AMD EPYC™ platforms.

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Published by kiriti-pendyala about 1 year ago

https://github.com/amd/zendnn-tensorflow-plugin - zentf Release v5.0.1

zentf 5.0.1 is the TensorFlow plugin which comes with ZenDNN 5.0.1, which is a minor release building upon the major ZenDNN 5.0 release. This upgrade continues the focus on optimizing inference with Recommender Systems and Large Language Models on AMD EPYC™ CPUs.

zentf 5.0.1 includes enhancements for bfloat16 performance, primarily by leveraging microkernels and operators from the ZenDNN 5.0.1 library. These operators are designed to better leverage the EPYC microarchitecture and cache hierarchy.

The zentf 5.0.1 plugin works seamlessly with TensorFlow versions from the latest 2.18 to 2.16, offering a high-performance experience for deep learning on AMD EPYC™ platforms.

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Published by kiriti-pendyala about 1 year ago

https://github.com/amd/zendnn-tensorflow-plugin - zentf Release v5.0

This release of AMD's CPU solution for TensorFlow provides a binary built with the Pluggable Device approach. This zentf release: - Supports TensorFlow v2.17. - Integrates with ZenDNN v5.0 as the core inference library and is compiled with GCC v12.2. - Merged BF16 and FP32 compute flows and added broadcasting support for BatchMatMul kernel. - INT8 support for the ResNet50 model. - Softmax kernel now supports up to 5D. - Deprecated blocked format support for convolution ops and restriction of rewrite for the fused ops based on the post ops. - Provides experimental support of C++ APIs.

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Published by kiriti-pendyala over 1 year ago

https://github.com/amd/zendnn-tensorflow-plugin - zentf Release v4.2

This zentf release:

• Is compatible with TensorFlow v2.16 and later.
• Extends TensorFlow to provide a performant AI inference solution for AMD EPYC^TM servers leveraging the ZenDNN v4.2 library.
• Includes graph optimizations and fusions tailored for AMD EPYC^TM architectures.
• Supports BF16 execution through auto-mixed precision to provide performance improvements with minimal changes in accuracy.

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Published by kiriti-pendyala almost 2 years ago

https://github.com/amd/zendnn-tensorflow-plugin - TensorFlow-ZenDNN Plugin Release v0.2

This is the first open-sourced release for TensorFlow-ZenDNN Plugin.

• This release supports the latest TensorFlow v2.14
• The backend library support in this release is upgraded from ZenDNNv3.3 to the latest released ZenDNN4.1
• This release continues to provide experimental support for leveraging the latest ZenDNN library via TensorFlow's pluggable device approach.

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Published by sanadani over 2 years ago