There are many use cases for AI in the data center, including improved safety and reliability, greater efficiency, and reduced energy consumption. By collecting information from infrastructure, AI can predict faults and respond in milliseconds.
As organizations around the world turn to digital transformation and innovation to pull ahead of the competition, many are upgrading and modernizing their existing IT infrastructure to deliver the new, fluid capabilities needed to support today’s hypercompetitive business environments.
This invariably includes a reevaluation of existing data centers, the specialized facilities built to support the smooth functioning of IT systems.
To drive digital transformation, a data center overhaul or revamp is often necessary to support power-hungry private cloud and hybrid cloud deployments.
The full-stack data center
Known for its telecommunications equipment used by 45 of the top 50 carriers globally, Huawei has invested substantial research and development (R&D) into communication technology (CT) and information technology (IT) systems over the last 30 years.
By combining its extensive ICT experience with deep data center knowhow, Huawei has developed a complete range of solutions from facility-level hardware for data centers to the IT equipment needed to support complex cloud systems.
This starts with modular data center systems for rapid deployment, to data center components such as UPSs, PDUs, cooling systems, and the DCIM software used to manage and operate them. A comprehensive suite of servers, storage and networking infrastructure is also available, as well as converged and hyperconverged platforms for scale-out deployments for a full-stack solution.
Huawei full-stack cloud platform
These aren’t hypothetical systems that have not been tested together. Built using prefabricated modules, Huawei’s own cloud data centers at Dongguan and Ulanqab in China are fully functional data centers built using Huawei’s full-stack data center solution, among deployments at other locations.
Crucially, Huawei is also a heavy contributor to the open-source OpenStack platform and has its own commercial FusionSphere distribution with enterprise-level enhancements for improved management and reliability.
Platform-as-a-Service (PaaS) capabilities also deliver a range of data enablement tools to support database and data warehousing implementations, while Software-as-a-Service (SaaS) offerings offer advanced big data and AI services such as visual and speech recognition.
Maintaining cohesiveness and integration across such a broad range of systems is a continuous effort, especially considering the sheer breadth and depth of the company’s offerings. To address this, Huawei has built OpenLabs for the enterprise market in Suzhou, Munich, Paris, Mexico City, Singapore, Dubai, Bangkok, Delhi, Cairo, Johannesburg, Moscow, and Istanbul. We are developing the best industrial solutions with customers and partners in different domains around the world.
iCooling analyzes a vast amount of historical energy consumption data to create a PUE prediction model
Understanding the rise of AI
With a good understanding of the application and trends of IT infrastructure and cloud service, Huawei has also incorporated advanced artificial intelligence (AI) capabilities into its range of data center facility offerings to further enhance the capabilities of its solutions.
Research from the McKinsey Global Institute says that AI has the potential to add about US$13 trillion to total economic output by 2030 and boost global GDP by about 1.2% per year. About 70% of global companies are expected to adopt at least one AI technology in the next decade, and more than 50% of global companies will adopt all AI technologies.
The rapid and widespread adoption of AI is staggering, and there is no question that it will become the core driving force behind the fourth industrial revolution.
Already, AI is spurring profound and potentially disruptive changes in the world, in diverse fields such as autonomous vehicles, smart digital assistants, home automation and digital marketing.
But how does AI fit into the data center? While the world is just getting started with exploring what AI can do, it turns out that there are many applicable use cases that can impact the data center. These range from using AI to improve safety and reliability, efficiency, and even in the reduction of energy consumption in data centers.
Pushing the envelope of AI in efficient energy use
Energy consumption is a top consideration for data centers everywhere. The increasing demand for high-performance computing across the industry is driving an increase in high-density servers, the use of GPUs, as well as specialized AI processing chips. These systems generate significantly more heat than traditional CPUs, making heat dissipation an increasingly vital topic in data centers.
This was the reason behind the development of Huawei’s iCooling intelligent thermal management solution for data center infrastructure. Before AI is introduced, various equipments such as air conditioners, chillers, cooling towers and water pumps are simply controlled by BMS to ensure the normal and safe operation. The cooling system, however, cannot run at the optimal efficiency point. Huawei iCooling system incorporates deep learning to draw the appropriate correlations between various cooling equipments with actual IT loads and environment variables.
The iCooling system achieves this by analyzing a vast amount of historical data and their impact on energy consumption to create a PUE prediction model. An optimization algorithm then establishes the ideal parameters which are transmitted to various control systems. At Huawei’s cloud data center Langfang in North China, the deployment of iCooling resulted in a PUE that is 8% lower, saving millions of renminbi in power costs annually.
Maximizing data center value with AI
One of the chief uses of AI is surely to improve the safety and reliability of data centers.
Before AI is introduced, the fault can be detected only after the component is faulty generally, affecting the UPS’s availability. By collecting information from the power supply and distribution system, AI-powered systems can predict impending device and component failures to warn operations and maintenance (O&M) personnel ahead of time, or to furnish additional information to aid decision-making.
On that front, the Huawei iPower intelligent power supply and distribution technology was developed to improve data center availability. Equipped with a response time measured in milliseconds, iPower can detect, isolate and recover from faults at sub-second speeds to eliminate fire risks and improve the reliability of a data center’s power infrastructure. It can also accurately predict battery lifespan and health, allowing preventive maintenance to be performed before they fail.
In a data center, IT devices are often deployed or removed from shelves, which brings a lot of fragmented resources, such as U space, which cannot be monitored or managed, and are easy to get wasted.
The AI-based iManager data center infrastructure management system uses intelligent hardware and IoT sensors to keep a close eye on the data center and reduce repetitive work through automation. The system manages resources such as power, cooling and space to optimize utilization, relying on AI to intelligently manage the allocation, deallocation, and operations of assets for improved operational efficiency and reliability. With the introduction of iManager, the resource utilization rate is increased by 20%.
Huawei iManager also supports network management, with centralized managing for multiple data centers across different locations. As edge data centers grow in popularity, this can reduce the need for site visits, allowing for more efficient data center management.
It should be no surprise that organizations that require infrastructure with the utmost reliability and performance turn to Huawei. Today, we have delivered more than 800 large data centers around the globe and provided customers with solutions that are efficient, reliable, simplified construction and smart O&M.
Source: Bob He (Data Centre Dynamics)