What is an NPU?
An NPU, or Neural Processing Unit, is a dedicated processor or processing unit on a larger SoC designed specifically for accelerating neural network operations and AI tasks. Unlike general-purpose CPUs and GPUs, NPUs are optimized for a data-driven parallel computing, making them highly efficient at processing massive multimedia data like videos and images and processing data for neural networks. They are particularly adept at handling AI-related tasks, such as speech recognition, background blurring in video calls, and photo or video editing processes like object detection.
NPUs are integrated circuits but they differ from single-function ASICs (Application-Specific Integrated Circuits). While ASICs are designed for a singular purpose (such as mining bitcoin), NPUs offer more complexity and flexibility, catering to the diverse demands of network computing. They achieve this through specialized programming in software or hardware, tailored to the unique requirements of neural network computations.
For most consumer products, the NPU will actually be integrated into the main CPU, as in the Intel Core and Core Ultra series or the new AMD Ryzen 8040-series laptop processors. At larger data centers or more specialized industrial operations, though, the NPU might be an entirely discrete processor on the motherboard, separate from any other processing units.
NPU vs. GPU
While many AI and machine learning workloads are run on GPUs, there is an important distinction between the GPU and NPU.
While GPUs are known for their parallel computing capabilities, not all GPUs are good at doing so beyond processing graphics, as they require special integrated circuits to effectively process machine learning workloads. The most popular Nvidia GPUs have these circuits in the form of Tensor cores, but AMD and Intel have also integrated these circuits into their GPUs as well, mainly for handling resolution upscaling operations — a very common AI workload.
NPUs, meanwhile, simply take those circuits out of a GPU (which does a bunch of other operations) and make it a dedicated unit on its own. This allows it to more efficiently process AI-related tasks at a lower power level, making them ideal for laptops, but also limits their potential for heavy-duty workloads that will still likely require a GPU to run.
The role of NPUs in different systems
NPUs are designed to complement the functions of CPUs and GPUs. While CPUs handle a broad range of tasks and GPUs excel in rendering detailed graphics, NPUs specialize in executing AI-driven tasks swiftly. This specialization ensures that no single processor gets overwhelmed, maintaining smooth operation across the system.
For instance, in video calls, an NPU can efficiently manage the task of blurring the background, freeing up the GPU to focus on more intensive tasks. Similarly, in photo or video editing, NPUs can handle object detection and other AI-related processes, enhancing the overall efficiency of the workflow.