AI Hardware Accelerators: Architectures and Implementation Strategies

Abstract

Artificial Intelligence also has achieved very rapid advancement, with computational power demands of the kind never before seen. However, continued demand on the specialized hardware has kept right on pace with how complex AI models have gotten. In this article, we dive into AI hardware accelerators architecture, the implementation strategy, and the amazing shift the world of AI got into.That burgeoning field has forced traditional computing architectures to their limit. General purpose processors are generally powerful in many ways other than dealing with the extremely difficult computational demands that AI algorithms require. As a result of this challenge, there is such a new class of hardware: AI accelerators. To enable breakdowns on areas such as computer vision or natural language processing, these are purpose built devices designed to reduce the time and energy required for computing with the AI significantly.To set AI hardware accelerator exploration in the space, we’ll evaluate the principles that govern their design, the type of accelerators that currently exist, and how to harness them to their largest deployment. Additionally we will also be envisioning future AI hardware, as well as some emerging trends we believe will define it. If you are a seasoned AI practitioner or just interested to know about the technology of the AI revolution, this detailed guide provides you some insights to the world of AI acceleration.