Future Computational Power of AI Hardware: A Comparative Analysis of GPUs and TPUs

Le résumé fourni par la source

In order to enhance artificial intelligence, as it is being developed further, more powerful computational resources are required. Within the scope of the hardware solutions for AI training and inference, the use of graphical processing units and tensor processing units has gained the most popularity and are now considered the most powerful. This paper discusses the architectural features as well as the merits and drawbacks of GPUs and TPUs, their current use in AI, and their expected future prevalence. Through a literature review, case studies, and performance analysis, this research will focus on the factors that are likely to influence the way artificial intelligence will be in the future and how the relevant hardware technologies could impact the industries.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.