WHAT ARE NPU PROCESSORS?

NPU stands for Neural Processing Unit, which describes a class of microprocessors that are specially designed to accelerate artificial intelligence (AI) applications, especially neural networks. They play a major part in running deep learning algorithms on devices efficiently.

Neural networks are the key technology powering modern AI. At the same time, they involve intensive mathematical computations that are not well suited for general-purpose central processing units (CPUs) in computers and mobile devices. Training and running neural networks require massive parallel processing of simple matrix math operations.

This is where NPUs come in – they act as specialized co-processors along with the CPU to handle AI workloads efficiently. NPUs have a parallel architecture with thousands of small processing cores optimized for running neural network operations quickly.

Top advantages NPUs offer are:

– Higher throughput for AI tasks compared to CPUs. Matrix computations in a neural network that may take a CPU tens of milliseconds can be done by an NPU in a few milliseconds.

– Lower power consumption as AI workloads are handled by dedicated low-power AI accelerators rather than the power-hungry CPU, which extends battery life.

– Constant availability of AI features on devices with an NPU even without an active cloud connection. Cloud offloading may cause latency.

Major companies like Apple, Samsung, Huawei, Google have already incorporated custom NPUs into their flagship mobile chipsets. The iPhone XS, Samsung Galaxy S10 all use NPUs to run real-time AI capabilities like image processing, AR, voice assistants without relying on the cloud.

Going forward, NPU adoption is expected to grow significantly with the rising deployment of AI and edge computing. As neural networks become ubiquitous, specialized hardware like NPUs that can run them quickly and efficiently without consuming too much power will be critical in bringing true artificial intelligence to devices people use every day.