What is the use of computing power, which has been so popular recently?

"In any method of calculation, you must first know its position. One vertical and ten horizontal, a hundred standing and a thousand rigid, a thousand and ten facing each other, ten thousand and a hundred equal." The mathematical work "Sun Zi Suan Jing" written about 1,500 years ago introduced the counting rules of counting rods in the form of rhymes. As the earliest computing tool in human society, the emergence of counting rods solved the practical needs of land reclamation and food exchange at that time. As human exploration continues to move forward, computing power is also continuously innovating and upgrading. Today, with the booming digital economy, computing power, like electricity, heat and water, is becoming an important support for the high-quality development of the economy and society.

In recent years, the term "computing power" has appeared more and more frequently in people's vision. With the acceleration of digitalization and intelligentization, the demand for computing power has become more urgent. Especially in the context of the rapid development of large models, the demand for computing power has ushered in a blowout growth.

According to the report "Puhui Computing Power Opens a New Computing Era" jointly released by KPMG and Lenovo Group, before the emergence of deep learning, the computing power used for AI training doubled approximately every 20 months; after that, the computing power used for AI training doubled approximately every 6 months; after 2012, the computing power demand for training global top AI models accelerated to doubling every 3-4 months, that is, the average annual computing power growth rate reached an astonishing 10 times; currently, the development of large models is in full swing, and the demand for training computing power is expected to expand to 10 to 100 times the original, and the exponential growth curve of computing power demand will be steeper.

What is Hashrate?

So, what is hashrate? And what is it used for?

Computing power is computing ability. From a narrow definition, computing power is the theoretical maximum number of floating-point operations per second (FLOPS) that a computer can achieve. However, computers not only have computing power, but also data storage and access capabilities, data exchange capabilities with the outside world, data display capabilities, etc. From a broad definition, computing power is the ability of computer equipment or computing/data centers to process information, and the ability of computer hardware and software to work together to perform certain computing needs.

At present, computing power appears in people's lives and work in the form of various devices, ranging from micro devices such as mobile phones and computers to data centers. As the carrier of computing power, chips directly determine the data processing speed and product performance.

1. Central Processing Unit (CPU)

The CPU is the brain of a computer or electronic device and handles all calculations performed by the computer, from simple arithmetic functions to complex data processing operations.

The CPU is responsible for fetching data from memory or storage, decoding instructions, executing commands, and then writing the results back to memory. Every software or application is eventually converted into machine code and then run on the CPU. The CPU interprets this code and turns it into actions or results.

The CPU receives inputs from various sources like keyboard, mouse, and other input devices. It then processes these inputs through various algorithms to provide the desired output. The CPU also controls system resources like memory, storage, and other hardware components like graphics and sound cards. It ensures that all these components work seamlessly to provide the desired user experience.

2. Graphics Processing Unit (GPU)

A GPU is a computer chip that renders graphics and images by performing fast mathematical calculations. GPUs are used in professional and personal computing. Traditionally, GPUs were responsible for rendering 2D and 3D images, animations, and videos, although they are now used more broadly.

In the early days of computing, central processing units (CPUs) performed these calculations. However, as more and more graphics-intensive applications were developed, their demands put a strain on the CPU and reduced performance, and GPUs were developed to replace the CPU in performing these tasks and improve the rendering of 3D graphics. GPUs work using a method called parallel processing, in which multiple processors handle different parts of the same task.

GPUs are well-known in PC gaming, where they allow for smooth, high-quality graphics rendering, but they are also used by developers to accelerate workloads in areas such as artificial intelligence.

3. Field Programmable Gate Array (FPGA)

FPGAs are programmable logic devices that can be reprogrammed to perform a variety of computing tasks, making them very useful in areas such as digital signal processing and cryptography. In addition, FPGAs are a type of integrated circuit (IC) that facilitates the creation of custom logic for rapid prototyping and final system design.

FPGAs differ from other custom or semi-custom ICs due to their inherent flexibility, which enables them to be programmed and reprogrammed via software downloads to adapt to the changing needs of the larger systems for which they are designed.

FPGAs are commonly used in areas such as edge computing, artificial intelligence, system security, 5G, factory automation, and robotics.

4. Quantum computing

Quantum computing is a new computing model that follows the laws of quantum mechanics to control quantum information units for computing. From the perspective of computable problems, quantum computers can only solve problems that traditional computers can solve, but from the perspective of computing efficiency, due to the existence of quantum mechanics superposition, some known quantum algorithms are faster than traditional general-purpose computers in processing problems. When applied to specific problems, quantum computers may find answers faster than classical computers.

Of course, each chip has advantages and disadvantages, and the choice of type depends on the needs of the task. For example, if you are performing a complex scientific simulation or machine learning algorithm, you might use a GPU or FPGA because they are well suited for such tasks.

The role of computing power

In recent years, with the development of the digital economy, data has gradually become a new factor of production, and computing power has become the core productivity, which has been widely used in various fields and levels of the economy and society. For example:

• Smart healthcare: The advancement of computing power will promote the intelligent and standardized development of the medical industry, greatly improving the efficiency and quality of medical services. In terms of medical data processing, computing power can provide powerful data processing capabilities, help medical institutions process huge amounts of medical data, and improve the efficiency of medical research and diagnosis. In terms of image processing, powerful computing power can provide faster image processing speeds and improve the accuracy and efficiency of diagnosis. In terms of telemedicine, computing power can support more efficient video calls and data transmission, bringing better telemedicine services.
• Smart city: computing power can help cities achieve intelligent management and operation, and improve the public quality and comfort of cities. In the field of smart transportation, computing power can help traffic management departments quickly process and analyze various types of traffic data, such as vehicles, pedestrians, traffic lights, etc., so as to make more effective traffic planning and scheduling decisions; in the field of public safety, computing power can be used to achieve video surveillance and intelligent analysis, and timely discover and deal with various public safety issues.
• Smart Manufacturing: Computing power can help manufacturing companies quickly process and analyze various types of industrial data, including production data, quality data, and equipment data, thereby improving production efficiency and product quality, and reducing costs and resource waste. In terms of intelligent quality control, computing power can accurately identify and prevent defects in the production process by analyzing quality data; in terms of intelligent supply chain management, computing power can help manufacturing companies achieve smarter supply chain management, thereby improving the flexibility and responsiveness of the supply chain.

It can be seen that as an important foundation support in the digital economy era, the role of computing power will become increasingly prominent, and empowering thousands of industries will gradually expand and deepen.

In conclusion:

Today, computing power is developing at an unprecedented speed. According to data released by the China Academy of Information and Communications Technology, the global computing power reached 429EFlops in 2020, with a growth rate of 39%. It is estimated that the global computing power will grow at a rate of more than 50% in the next five years, and the overall scale will reach 3300EFlops by 2025.

What is certain is that as technology continues to develop, computing power levels will be further improved and optimized, playing a vital role in shaping technology and innovation in the coming years.