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The trend of large models is sweeping across the world, and some industries have begun to reconstruct based on large models. In the future digital world, artificial intelligence will undoubtedly play an important role. By combining with different basic technologies and products, artificial intelligence will promote continuous technological innovation in various fields, and the operating system as the core basic software is no exception. At the 2023 Operating System Conference and openEuler Summit, we found that openEuler has already laid out its plans in advance, leading the intelligent future in the digital era
OpenEuler has always focused on investing in root technology to build a solid software foundation for thousands of industries. Currently, the cumulative installed base of openEuler has exceeded 6.1 million units, making it the first open source operating system to change the landscape of software operating systems. According to IDC predictions, openEuler will rank first in China's server operating system market share in 2023, reaching 36.8%. Facing the future of digital intelligence, openEuler is fully integrated with AI to create a full-scenario operating system for digital infrastructure, providing technical convenience to more users.
Facing the new era of intelligence
openEuler enables AI to be more efficient
In the past four years, the openEuler community has experienced rapid development. According to Xiong Wei, vice chairman of TOC of the Open Atom Open Source Foundation and executive director of the openEuler Committee, in the early days of the openEuler community, there were only two to three hundred active developers every day, but now it has attracted more than 16,800 open source contributors, and more than 4259 active users. These developers provide extensive assistance with system features, innovations, and bug fixes. In addition, the openEuler community has accumulated more than 1,300 cooperative enterprises and partners
Xiong Wei is the Vice Chairman of TOC of the Open Atomic Open Source Foundation and the Executive Director of the openEuler Committee
As more and more users and partners join the openEuler community, where will openEuler develop in the future? In the past, openEuler had two main technical pillars, namely full scenarios and diverse computing power. With the continuous development of new technologies such as large models, openEuler has added a third technical pillar, namely intelligence. Digital openEuler will gradually evolve into intelligent openEuler, becoming the next generation operating system for the era of diverse computing power and intelligence
The boundaries of intelligence continue to expand. As a bridge between hardware and applications, operating systems embrace the future of digital intelligence and combine with AI is an inevitable trend.
Hu Xinwei, chairman of the openEuler Technical Committee, said that under the current hardware trend, more and more intelligent and diverse computing power needs to achieve efficient collaborative work, and at the same time, more and more ubiquitous intelligent applications need to be quickly intervened. In order to realize this vision, openEuler hopes to achieve the effects of zero threshold, zero loss and zero intervention. For ordinary users, when deploying and installing smart applications, they hope to achieve a "zero" threshold; for smart applications to run on diverse computing power, the operating system should allow smart computing power to achieve "zero" loss; in smart applications During the daily operation and maintenance of applications, system administrators should achieve "zero" intervention in the daily work of the system
Therefore, openEuler implements full-stack AI enablement through "openEuler for AI" and "AI for openEuler" to create a containerized, ready-to-use solution.
"openEuler for AI" is an expansion of ecological boundaries. In the future, openEuler will comprehensively enhance its compatibility with AI, support more mainstream intelligent applications and large language models, and achieve intelligent capability upgrades. It is not easy to build an AI ecosystem. At present, we can see that some AI products, technology ecosystems, infrastructure, etc. are fighting independently. However, as the market gradually matures, AI full-stack enablement is an inevitable result of future development.
Full-stack enablement will allow openEuler users to use the containerization solution provided by openEuler out of the box when using smart applications in the future. At the same time, it can also automatically adapt to the hardware environment to achieve optimal performance. openEuler's full-stack enablement also includes two levels of meaning. The first is the optimization of support for various applications, models, tools, and frameworks, such as vector databases such as AquilaDB, popular large models in the industry such as Llama and ChatGLM, tool chains such as cuda, rocm, and openvino, and AI frameworks such as PyTorch and TensorFlow. In addition, due to the complexity of AI hardware, openEuler also provides extensive support for AI hardware compatibility. A series of upgrades will greatly improve users' AI development and usage efficiency.
In terms of developer support, openEuler continues to optimize the usability and adaptability of AI. It provides functions such as containerized packaging and one-click image pulling, allowing developers to easily deploy AI environments and achieve zero threshold
Currently, we have entered an era of diverse computing power. The common development of software and hardware gives room for redesign of operating system scheduling. Through the SMT architecture of the CPU, the operating system is given the opportunity to pre-deploy tasks, and the GPU can also avoid problems such as suspension through hardware warp switching. Therefore, how to bring together independent heterogeneous devices, uniformly allocate resources, and solve the waste of computing power and the complexity of heterogeneous memory programming is an important issue.
In the traditional sense, different heterogeneous computing powers are completely separated from each other in terms of memory management, and it is difficult to share them with each other. Another important value of "openEuler for AI" is heterogeneous fusion. Its core idea is to bring together independent heterogeneous devices and uniformly allocate resources to solve the two problems of serious waste of computing power and complex heterogeneous memory programming. Through the heterogeneous kernel management introduced in openEuler, unified addressing can be achieved between the CPU and NPU by sharing page tables, allowing both parties to use memory with each other and achieve "transparent" memory expansion and super-resolution, which can improve the throughput of inference scenarios. The throughput is increased by 50%, and the demand and cost of memory management are greatly simplified. Multiple sets of memory interfaces in the past are simplified into one set, and heterogeneous driver code can be reduced from 10,000 lines to 100 lines.
The collaborative development of large models and operating systems has become a trend
AI empowers openEuler to be smarter
Judging from this year’s technological development, large models allow more people to see new possibilities in operating systems. For example, in 2023, Microsoft announced that it would embed the GPT-4 large model into Windows to upgrade the operating system from graphical interaction to natural language interaction, which is expected to change the system interaction method that has been used for nearly thirty years. Windows Copilot will land on the taskbar in Windows 11 to help users find and change settings more easily, avoiding the constraints of cumbersome options and operating procedures.
On the cloud, traditional complex operation and maintenance work is also expected to be changed by large models. The analysis of cloud fault root causes and the formulation of mitigation measures based on large models have performed well, and have been recognized by more than 70% of operation and maintenance personnel; in terms of task collaboration, the software open API is provided to AI to control the completion of complex tasks, achieving a goal beyond that of assistants and The excellent performance of the tool can increase the overall system value.
As artificial intelligence innovation technologies represented by large models and large computing power continue to develop, AI continues to accelerate its entry into thousands of industries, and operating systems also need to continue to evolve towards AI. In this context, collaborative optimization of large models and OS has become a trend, the operating system will undergo major changes, and digital openEuler will evolve into smart openEuler.
Smart openEuler brings changes in system interaction. For example, developers may use various programming languages in their daily work, but no one of them is as natural and convenient as our native language. So, is it possible to use tools to realize the interaction between natural language and the operating system, thereby reducing the intensity of writing scripts, configuring parameters, or debugging? openEuler uses the ChatGLM basic model and trains EulerCopilot based on a large amount of openEuler code and data. It initially implements functions such as code-assisted generation, intelligent problem analysis, and system-assisted operation and maintenance, making openEuler more intelligent. EulerCopilot will bring about huge changes in the interaction between humans and machines, and this is also an important change in "AI for openEuler"
If "openEuler for AI" has brought new vitality, then "AI for openEuler" has injected new vitality. Based on the technology accumulated by the openEuler community, EulerCopilot provides users with more convenient artificial intelligence capabilities and rich job portals. Users can interact through public accounts, WEB interfaces, SHELL, IDE, etc. EulerCopilot integrates massive knowledge in the OS field and can answer various professional questions from developers, automatically complete unfinished code segments, and even complete requests such as "system performance diagnosis", and automatically generate diagnostic reports and tuning opinions
The unimaginably vast space
In the future of digital intelligence, openEuler will serve as a platform to continuously input artificial intelligence capabilities into various application scenarios such as servers, clouds, edge computing, and embedded systems to promote digital upgrades in all walks of life. Of course, realizing a digital intelligence future requires different infrastructure. Wu Fengguang, a member of the openEuler open source community technical committee, said: "In the era of artificial intelligence, the community is moving towards intelligent collaboration, and we are exploring how to empower community collaboration through artificial intelligence." openEuler has built Infrastructure 2.0 to support global development, full-scenario construction and full-link collaboration to help more people acquire artificial intelligence capabilities
In addition, openEuler’s important development direction is overseas expansion and globalization. Wu Fengguang said that when openEuler was founded, it decided to fully globalize. After focusing on independent innovation in China, it would go overseas to gather global developers and come to the openEuler community for native development. Therefore, the Open Atomic Foundation has formed connections with many foundation organizations and upstream community projects to conduct version certifications and complete project work for each other. Only in this way can we continue to gather global open source forces and contribute Chinese wisdom to the world's open source.
Since the operating system (OS) source code adopts a new architecture, it needs to be converted from SPEC (specification) to YAML (a configuration language), which will help build full-scenario capabilities. The advantage of YAML is its versatility and low threshold. This means that more developers can use it, almost everyone can use it, and a large user base can be quickly established. As a universal configuration language, YAML can also be used to create out-of-the-box customization capabilities, support the customization of any YAML field, and adapt to upstream software in many formats. In addition, the operating system also supports layered customization to build software for multiple scenarios through EulerMaker and EulerTest
In order to solve the problem of difficulty in promoting upstream software to users and the problem of users’ voice not being transmitted smoothly to upstream, openEuler has opened up the link from upstream to users through the application software platform in terms of infrastructure, realizing a full chain in the true sense. Road collaboration. This is obviously not the ultimate form of openEuler. It is expected that in May 2024, openEuler will release the 24.03LTS version of the new kernel to further improve its full-scenario capabilities. Using Linux6.6 as the kernel to achieve ecological unification. Create a new EEVDF scheduler and folio memory management mechanism to further improve scheduling and memory usage efficiency. There are comprehensive improvements in IO management, new network standard support and support for CXL.
In order to adapt to different usage scenarios, the 24.03LTS version will provide different optimization upgrades. In cloud computing scenarios, through CPU aggregation scheduling, low-load computing power can be intelligently aggregated to achieve collaboration between load and computing power. In addition, a cloud-native minimum set release version supporting openEuler will be provided, supporting one-click deployment. In the embedded scenario, the original open source project MetaBMC for server BMC will be released, and a standardized development board "openEuler Pie" with native built-in openEuler and an industrial robot framework "openEuler arm" will be provided
In the field of AI, openEuler will continue to develop. In addition to EulerCopilot, intelligent tuning of the operating system will also be implemented, which will be of great help to developers. By sensing business characteristics and dynamically adjusting scheduling priorities, configuration parameters and other optimization strategies during application operation, scenario-based performance improvements of more than 15% can be achieved
As far as I can see, I can see friends coming from afar. The development of AI has never been driven by one company or one community. openEuler will promote industry development by establishing learning groups, formulating new specifications and other measures, and is committed to becoming a leader in the AI field. When AI and OS achieve each other, future developers will be expected to create greater value and complete more technological innovations.
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