How To Test NPUs

What are NPUs? Why do you want to use NPUs? How do you test them?

Photo by Vishnu Mohanan on Unsplash

NPU stands for Neural Processing Unit and it is a special hardware (aka, AI Accelerator) for Artificial Intelligence. It is gaining more popularity among AI companies as a way to overcome GPU bottlenecks. There is more need to test and evaluate AI model performance in NPUs. This article is meant as a guideline for testing NPUs.

1. Limitations of GPU

So far, NVIDIA’s GPU dominated the AI hardware market for years. Its special hardware allowed parallel processing of AI models possible and was the single most important contributor to the rise of AI in recent years. However, GPUs have a few problems. Here are a few that are often mentioned in the context of using NPUs instead.

1. Expensive: A popular 3090 Ti costs about $2,000 at a minimum. That could be a sticker shock for many amateurs and AI startups.
2. Powerful: Power is good for AI training and gaming but it also consumes a lot of electricity.
3. Heat: More electricity also generates a lot of heat and to cool it down, you need an extra cooling system.
4. Big: With its power and generated heat, the cooling system tends to be big too which results in its overal big size.