What is the difference between computing power scheduling and cloud computing
The research report released by Canalys shows that in the second quarter of 2023, the global cloud infrastructure service expenditure will increase by 16%, reaching $72.4 billion.
Previously, the rapid growth of cloud manufacturers was mainly attributed to large-scale enterprise digital transformation and cloud deployment. At present, the growth rate of the market is slowing down. In addition to the peak of market growth brought by the popularization of cloud, it is also closely related to the uncertainty of the global macro-economy. Cost reduction and efficiency increase have become the mainstream. Enterprises tend to adopt conservative IT strategies, and expenditures have declined significantly. At the moment of fierce market competition and price war, cloud manufacturers need a new direction of market growth. The big model explosion brought by ChatGPT can be said to be timely.
However, the AI big model boom and the popularization of AI applications have triggered a computing power gap. At the same time, AI computing centers that provide model development and training platforms also have higher requirements. We see that cloud manufacturers have joined the battle and started to deploy computing power. In addition to Alibaba, Tencent and other large manufacturers, UCloud Youkede, Qingyun and other scientific and innovative listed enterprises have also deployed here. So, what is the difference between computing power scheduling and cloud computing?
1、 In terms of definition and core functions
Computing power scheduling is a new information infrastructure based on the on-demand allocation and flexible scheduling of computing resources, storage resources and network resources among cloud, edge and end. It covers a wide range of fields from general-purpose computing to high-performance computing (HPC).
In contrast, cloud computing is an Internet based computing method, which provides computers with various terminals and other devices on demand by sharing software and hardware resources and information. The person in charge of relevant business of Qingyun believes that the connotation of computing power service is more extensive, including general computing power, intelligent computing, supercomputing and other forms of computing power. It is also a "noun" that has become more concerned with the concept of digital economy and computing power economy. The elastic expansion, operation and maintenance and other technical capabilities and practical experience of cloud computing can also provide reference for the overall computing services and support the realization of computing inclusive.
2、 Technical scenario and implementation scenario
For computing power scheduling, computing power scheduling focuses more on the execution of high-performance computing tasks, and is applicable to scientific computing, engineering computing, intelligent computing and other fields.
Cloud computing, on the other hand, focuses more on providing easily scalable and often virtualized resources, enabling enterprises to quickly deploy applications, reducing management complexity and maintenance costs.
The relevant business leaders of UCloud Youkede believe that the technical differences are:
1. Computing services pay more attention to the provision and management of computing resources, including high-performance computing, large-scale data processing, etc., while cloud services are more comprehensive, including computing, storage, networking, and other aspects.
2. Computing services usually need to provide higher performance hardware devices and optimized computing environments to meet the needs of large-scale computing.
The service differentiation is:
1. Computing services are more focused on providing computing resources, providing more flexible computing scale and billing mode to meet users' needs for high-performance computing.
2. Cloud services are more comprehensive, providing more service components, such as storage, database, artificial intelligence, etc., to meet the diverse needs of users.
3、 Future development trend
With the development of data economy, the prediction that global data will increase by 1YB every year in 2030 shows a huge demand for computing power.
Cloud computing relies on resource sharing to achieve economies of scale. Service providers integrate a large number of resources for multiple users, and users can easily request more resources according to their needs.
4、 Characteristics of the Chinese market
In China, the rapid development of digital infrastructure is promoting the integration of computing power and cloud computing. The government and enterprises are actively laying out a computing network to support digital transformation. For example, the Computing 2030 released by Huawei predicted that the computing power of artificial intelligence would increase 500 times over 100ZFLOPS, which reflects the important position of China in the construction of global computing network.
In addition, cloud manufacturers also have their own advantages and disadvantages in computing power scheduling.
Qingyun believes that cloud manufacturers were mainly engaged in general computing before, and intelligent computing is a new round of investment, with new requirements for capital and technology. It is also from the reality that Qingyun chooses to participate in the AI computing tide from the computing power scheduling that has accumulated technology and successfully landed experience.
UCloud also made its own thinking summary. First of all, the Intelligent Computing Center needs to invest a lot of money and resources to build high-performance hardware equipment and optimized computing environment, including servers, network devices, storage devices, etc. At the same time, it is necessary to ensure the reliability and stability of the equipment to meet the needs of users for high-performance computing.
Secondly, the intelligent computing center needs to have advanced computing technologies and algorithms to provide high-performance computing services. Cloud manufacturers need to constantly carry out technology research and innovation to cope with changing computing needs and algorithm development.
Third, the data and computing tasks processed by the intelligent computing center often involve users' privacy and sensitive information. Cloud manufacturers need to take strict security measures to protect the security of users' data and computing tasks. At the same time, it is necessary to comply with relevant laws and regulations to ensure data compliance. The self built data center provides a highly secure and reliable infrastructure environment to ensure data security.
Fourth, the construction and operation of the intelligent computing center need a lot of investment, Virtual machine Cloud manufacturers need to control costs and improve resource utilization to achieve economic benefits. At the same time, we need to develop a reasonable billing model to meet the needs of users and ensure our profitability.
In addition, the competition in the smart computing center market is fierce, and cloud manufacturers need to constantly improve their competitiveness to meet the changing market demand. At the same time, it needs to compete differently with other cloud vendors to provide unique values and solutions.
From the above analysis, we can see that computing scheduling and cloud computing are different in technology and application. Cloud computing is becoming the core of IT strategy, while computing scheduling is more focused on the execution of high-performance computing tasks. However, they together form the foundation of the digital economy. This differentiated integration provides a strong support for digital transformation. Together, they form the cornerstone of the digital economy, indicating a more intelligent and efficient future. So, where does your understanding of differentiation lie?
