zentorch 5.0.0

zentorch : A PyTorch* extension for AMD EPYC CPUs.

The latest ZenDNN Plugin for PyTorch* (zentorch) 5.0 is here!

This powerful upgrade continues to redefine deep learning performance on AMD EPYC™ CPUs, combining relentless optimization, innovative features, and industry-leading support for modern workloads.

zentorch 5.0 takes deep learning to new heights with significant enhancements for bfloat16 performance, expanded support for cutting-edge models like Llama 3.1 and 3.2, Microsoft Phi, and more as well as support for INT4 quantized datatype. This includes the advanced Activation-Aware Weight Quantization (AWQ) algorithm, driving remarkable accuracy in low-precision computations.

Combined with PyTorch's torch.compile, zentorch transforms deep learning pipelines into finely-tuned, AMD-specific engines, delivering unparalleled efficiency and speed for large-scale inference workloads.

The zentorch 5.0 plugs seamlessly with PyTorch version 2.4.0, offering a high-performance experience for deep learning on AMD EPYC™ platforms.

Support

We welcome feedback, suggestions, and bug reports. Should you have any of the these, please kindly file an issue on the ZenDNN Plugin for PyTorch Github page here

License

AMD copyrighted code in ZenDNN is subject to the Apache-2.0, MIT, or BSD-3-Clause licenses; consult the source code file headers for the applicable license. Third party copyrighted code in ZenDNN is subject to the licenses set forth in the source code file headers of such code.