In the past, we talked about two important hardware components in computers, namely the CPU (Central Processing Unit) and GPU (Graphics Processing Unit). Now, we are increasingly discussing NPU. So, what is NPU?
01What is NPU?
Many people are familiar with CPUs and GPUs, but not so much with the recently popular NPU. In fact, NPUs have been shining in the mobile chip field for quite some time.
The Neural Processing Unit (NPU) is a chip specifically designed to accelerate artificial intelligence (AI) and machine learning (ML) applications, aiming to efficiently and low-power execute machine learning tasks, especially deep learning tasks.
It can simulate the working principles of the human brain’s neural networks, achieving acceleration of complex calculations such as large-scale matrix operations and convolution operations in deep neural networks through large-scale parallel processing units (similar to neurons) and efficient interconnection structures (similar to synapses). In simple terms, it simulates all possible solutions and selects the optimal one.
The standard for judging NPU speed is TOPS, which stands for “trillions of operations per second.” TOPS is an indicator that demonstrates the computational capability of the processor by quantifying the number of operations (including addition, multiplication, etc.) executed by the NPU in one second. The calculation of TOPS can reflect the efficiency and performance of the NPU when handling AI tasks.
02Differences Between NPU, CPU, and GPU
As we know, the CPU is the core processor of a computer system, used to execute a wide range of general computing tasks. Its advantages lie in its powerful control logic and efficient single-threaded performance, making it suitable for handling complex logic and control tasks. However, the CPU has limited parallel computing capabilities and is relatively weak in executing specific tasks such as AI computations.
The GPU is designed for graphics rendering, with a large number of built-in parallel computing units that can efficiently handle a large number of simple, repetitive computing tasks. Since many computational operations in deep learning (such as matrix operations and convolution operations) are similar to graphics rendering, GPUs perform excellently in AI tasks. However, the GPU architecture is not fully optimized for AI tasks, and its efficiency is far less than that of NPU when handling certain types of AI tasks.
NPU is a processor specifically designed for artificial intelligence and machine learning scenarios, with targeted optimizations in hardware structure, focusing on executing AI-related computational tasks such as neural network inference, and achieving higher energy efficiency.
For example, in video conferencing applications, NPU technology can easily achieve features like intelligent background removal and background blur switching. If a GPU were used for these computations, it would be very complex, slow in processing speed, and high in energy consumption.
03What Role Does NPU Play in AI PCs?
AI PCs are gradually changing the landscape of traditional computers. With the addition of NPU, whether it is voice recognition, language translation, or text generation, the response speed and accuracy can be significantly improved. In creative applications, it can also accelerate complex filters and effects, significantly enhancing video rendering speed, making the creative process smoother and more efficient. In AR and VR application fields, AI PCs provide strong computational support for building virtual worlds and enhancing real-world displays, making virtual reality more vivid.
Importantly, NPU accelerates the execution of personalized recommendation algorithms, allowing AI PCs to analyze user behavior data in real-time, providing highly personalized recommendation services, resulting in a more intelligent user experience.
In summary, with the rise of AI PCs, it marks a shift towards more intelligent and personalized personal computers, and NPU is an important force driving the development of artificial intelligence technology. With continuous technological advancements and expanding applications, NPUs will play an increasingly important role in future computing architectures, providing strong support for the intelligent transformation of various industries.
The HP EliteBook X G1i and HP EliteBook X Flip G1i commercial laptops are equipped with Intel® Core™ Ultra processors, capable of achieving 48 TOPS of NPU computing power, allowing for the processing of a larger volume of AI tasks directly on the laptop, providing more efficient and intelligent services.
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