Machine Learning hardware- Understanding performance analysis and comparative study of different specialized hardware

Machine Learning is a method that provides systems the ability to generalize and extract meaningful information from data. Advancements in multicore processors and accelerators have opened the gates of Machine Learning techniques to be used in fields like Speech recognition, Image Processing, Computer Vision, Autonomous driving etc. These processors and accelerators are available in many forms like, from CPUs and GPUs to ASICs, FPGAs, and dataflow accelerators.

This whitepaper discusses various Machine Learning hardware stakeholders and a comparative analysis of how each one fares in the ever-growing field of neural networks with focus on Deep Learning.  Some of the key topics this article covers are following:

• Hardware for Machine Learning/ Deep Learning
• Google Tensor Processing Unit (TPU)
• GPUs from NVIDIA
• Intel Xeon Scalable processor
• Intel Movidius
• Intel® Arria® 10 FPGAs
• Intel® Nervana™ Neural Network processors
• Goya Architecture

• Performance Analysis

Download whitepaper now to understand the comparative study and performance analysis specialized hardware for Machine Learning.