What are AI Chips? A Comprehensive Guide to AI Chip Design
There’s a lot of talk about AI these days and how it is transforming everything from the workforce to medicine, space exploration, and our lifestyles. AI is infiltrating all facets of technology. It’s increasing the capacity of the data center to run vastly expanded workloads with greater levels of complexity more efficiently than ever before. It is simultaneously giving birth to computing at the edge and transforming the internet of things. But what exactly are AI chips and why are they so significant in our ability to advance to a new age?
Today’s AI chips run AI technologies such as machine learning workloads on FPGAs, GPUs, and ASIC accelerators. They can handle many more variables and computational nuances, and they process exponentially more data than conventional processors. In fact, they are orders of magnitude faster and more efficient than traditional integrated circuits (ICs) for data-heavy applications.
There has been a revolution in semiconductor architecture to make AI chips happen. The latest advancement is to architect AI chips into many separate, heterogeneous components—optimized for their unique function—in a single package. These multi-die systems break the limitations of traditional monolithic SoC designs which are fast reaching their performance ceiling. In fact, these multi-die systems are cornerstone in enabling deep learning capabilities.
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