Glossary What is a Neural Processing Unit (NPU)?

An NPU, or neural processing unit, is a specialized processor chip optimized to perform the complex calculations required for deep learning algorithms — supporting fast execution of complex AI tasks.

While the evolution of AI technology has surged in recent years, neural network accelerators have been installed in devices since the 1990s. However, it wasn’t until the late 2000s that neural processing units were increasingly deployed to accelerate machine learning tasks. The term NPU has gained even more importance in recent years as AI-powered devices and tasks have become more prevalent.

Often, a neural processing unit is also labelled as an “AI accelerator” or “deep learning processor,” but the functionalities are still very much the same.

NPUs are found in the hardware of everyday smartphones, personal computers and cloud computing servers. As more industries and businesses adopt AI, the demand for NPUs with a higher performance capacity has increased. Understanding the capabilities and limitations of an NPU is crucial for businesses looking to invest in AI hardware and stay ahead of the competition.

Here are the highlights of a neural processing unit organizations must understand when refreshing hardware:

• NPUs handle complex AI workloads with minimal power consumption, making them a cost-effective solution for businesses looking to adopt AI-ready technology.
• NPUs can be integrated into a wide range of devices, from smartphones to data centers, providing businesses the flexibility for AI processes in their IT infrastructure.
• The performance of NPUs is measured in TOPS, a key metric for evaluating the performance of AI processors and accelerators.

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