By Sally Ward-Foxton, EETimes
October 31, 2019
First, determine if you need one.
As more and more companies begin to use machine learning as part of normal business operations, those investing in their own hardware for whatever reason are now faced with a choice of different accelerators as this ecosystem begins to expand. When choosing between the very different chip architectures that are coming to the market, performance, power consumption, flexibility, connectivity and total cost of ownership will be the obvious criteria. But there are others.
Last week I spoke with Alexis Crowell, Intel’s senior director of AI product marketing, on this topic. Intel offers various AI accelerator products with completely different architectures (including, but not limited to, Movidius, Mobileye, Nervana, Loihi, not to mention all the CPU products). Crowell was happy to highlight some of the less obvious criteria that should be considered when choosing an AI accelerator.