AI Intelligence Data Center
Empowering AI and Digital Economy Integration through Scalable Computing Solutions
The construction of intelligent computing centers can not only promote the application of AI technology across various industries but also facilitate the deep integration of the digital economy with the real economy, thereby laying a solid foundation for the development of a smart society and the advancement of intelligent industries. This plan seeks to establish operational, efficient, and flexible multi-intelligence computing centers, addressing the key bottlenecks in the construction and operation of traditional data centers. It aims to provide comprehensive support for the development of intelligent computing centers of various scales, including regional and industry-specific intelligent computing centers.
Capabilities
Unified Resource Management for AI Workloads
Enable centralized management of heterogeneous resources, including GPUs, CPUs, and storage. Dynamically allocate and monitor resources to optimize utilization, reduce costs, and improve task execution times in AI and big data applications.
Efficient Task Scheduling and Execution
Implement intelligent scheduling to minimize task delays and enhance resource efficiency. Utilize real-time performance monitoring and automated scheduling to streamline operations across diverse computing environments.
Rapid Deployment and Scalability
Support fast application deployment with flexible cloud services. Provide on-demand scalability to accommodate fluctuating workload demands while ensuring operational stability.
Real-time Performance Monitoring and Cost Optimization
Monitor resource performance and usage in real-time through visualized dashboards. Implement cost control strategies by identifying inefficiencies and optimizing resource allocation.
Open Framework for Innovation
Provide a development platform that supports quick access to pre-built frameworks, enabling developers to rapidly build, train, and deploy AI applications. Facilitate integration with third-party tools for customized solutions.
AI-powered Industrial Transformation
Leverage AI computing clusters to modernize traditional industries. Enable digital transformation through tailored applications for logistics, energy, and manufacturing sectors.
Enhanced Public Services and Governance
Deploy AI solutions to improve public service delivery and social governance. Use intelligent systems to streamline administrative tasks and enhance citizen engagement.
Accelerated AI R&D and Model Training
Offer a one-stop platform for AI model development, from data preprocessing to deployment. Reduce development cycles and empower innovation by providing robust computing resources.
Digital Infrastructure for Ecosystem Growth
Build a stable and secure digital platform to support ecosystem-wide applications. Enhance collaboration between stakeholders by providing seamless data storage and sharing capabilities.
Customizable AI Solutions for Diverse Needs
Enable organizations to develop AI solutions tailored to specific use cases. Support fine-tuning of large language models and training of independent small models to meet unique business requirements.
Challenges
High and Ongoing Costs
The initial investment in hardware facilities is huge, and with rapid technological iteration, the equipment update cycle is shortened, which increases cost uncertainty.
Complex Technology
Achieving deep optimization and high coordination in software and hardware architecture is difficult. Challenges include solving problems with high-speed transmission, efficient storage, and real-time analysis of large-scale data.
Improved Operational Efficiency
Operators need to continuously reduce costs and improve efficiency, while facing difficulties in commercial monetization. They require diversified marketing, data analysis, and pricing strategies to expand and maintain customers.
The Dilemma of Standardization and Compatibility
Cross-manufacturer technical barriers lead to a closed ecosystem, limiting computing power scheduling and service flexibility.
Diverse and Changing Application Requirements
The need to adapt to ever-changing current and future demands requires high adaptability and foresight in addressing diverse application requirements.
Advantages
Unified Scheduling of Multi-location and Multi-resource Computing Power
The intelligent computing platform centrally manages the scheduling of computing power across multiple locations, supporting AI computing with diverse hardware, high-speed networks like InfiniBand and RoCE, and local NVMe and parallel file storage, enhancing cross-regional deployment and resource utilization.
Efficient and Intelligent Resource Scheduling
The intelligent computing platform features distributed scheduling and management capabilities that automatically allocate and manage computing resources. This optimizes task execution time and boosts work efficiency, enabling users to focus on business innovation and application development.
Support for Heterogeneous Domestic Chips and Diverse Resources
The platform supports the unified management of diverse servers, storage, and security devices, and integrates GPUs from multiple manufacturers. It provides robust computing power for a wide range of applications, fostering innovation across industries.
Simplified Operations with Intelligent Resource Management
Through a unified platform, resources are standardized, visualized, and efficiently managed, allowing for accurate resource allocation and standardized service operations. Multi-dimensional monitoring enhances computing efficiency and simplifies operation and maintenance.
Open and Ecological Support for AI Applications
The platform offers an open application framework and model services, integrating ecological applications from various manufacturers to provide a rich AI computing environment. This enables users to implement AI across diverse business scenarios and enhances the application of SaaS services.