April 2024
Intermediate to advanced
400 pages
12h 57m
English
In the ever-advancing realm of computational technology, specialized hardware components like graphics processing units (GPUs), field programmable gate arrays (FPGAs), and a plethora of other accelerators are making notable strides. Often termed “exotic hardware,” these components are just the tip of the iceberg. Cutting-edge hardware accelerators, including tensor processing units (TPUs), application-specific integrated circuits (ASICs), and innovative AI chips such as Axelera,1 are reshaping the performance benchmarks across diverse applications. While these powerhouses are primarily tailored to supercharge machine learning ...