Project Purpose

The project involves work within TensorFlow and related technologies. The effort involves work related to simple enablement to optimized efforts to maximize performance.

Project Details

Overview

The TensorFlow project is hosted out of the LDCG segment group. The project involves work within TensorFlow. The effort involves simple enablement to optimized efforts to maximize performance.

Scope

Data Center hardware powered by Arm designs could be found across the ecosystem. From the very high end Fugaku super computer, cloud computing, and other forms, these devices can be utilized for AI training and inference. These devices are often multi node, many cores, with or without specialized offload.

Edge devices are comprised of a wide variety of Cortex-A equipped hardware. These devices might be running Android, Linux and every other operating systems. Within this class of devices their capability to performance AI workloads such as inference can vary greatly. On the low end memory might be tight and no offload exists to on the high end, they can be server like with offload and plenty of resources. Indeed Edge devices since they are Cortex-A can have quite a bit in common with HPC/Server with the exception that one does not generally perform training on an edge device.

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