Enterprise-level computing center
Empowering Enterprises with GPU-Driven Solutions
The GPU computing power pooling solution forms a GPU resource pool by centrally managing multiple homogeneous or heterogeneous GPU servers. This resource pool realizes unified management and dynamic allocation of GPU resources through the resource management and scheduling system. Help enterprises build a multi-computing center. By integrating multiple GPU resources and relying on management and scheduling algorithms and technologies, it provides flexible and reliable computing support for various enterprises and institutions to meet the AI implementation needs in the fields of artificial intelligence, scientific computing, and drug development. With full-process support from model pre-training, model fine-tuning to model reasoning, enterprises can easily cope with the ever-changing AI challenges and achieve innovative development.
Capabilities
Resource Planning and Optimization
Organize and manage existing resources by service type. Newly acquired resources are planned and optimized for network and business needs, ensuring rational use based on configuration and quantity. Resources are categorized by chip type and business volume of parallel computing, with optimized scheduling for NVLink and IB networks.
Distributed Integration and Scheduling
Utilizes a distributed architecture to aggregate and manage heterogeneous computing resources. Supports integration, scheduling optimization, and dynamic scalability to meet diverse user and application needs across various scenarios.
High-Performance Heterogeneous Computing Support
Provides unified management of diverse computing resources, including GPUs and NPUs, forming a flexible computing pool to meet complex business requirements. Supports GPU virtualization and various delivery solutions for different scenarios.
Reliable and Flexible Networking
Enables hybrid network architectures and topologies for stable and reliable data transmission. Ensures system availability and operational stability through collaborative multi-node operations.
User-Centric Self-Service Computing
Supports flexible application and allocation of computing resources. Users can leverage cloud hosts, AI, and HPC computing power based on their requirements and pay-per-use for scalability and cost efficiency.
Simplified Management for Innovation
A unified operation and maintenance platform reduces complexity and operational costs, enabling businesses to focus on innovation and development by simplifying resource management.
Challenges
Resource fragmentation and inefficient utilization
Enterprises face the problem of scattered computing resources and low utilization, making it difficult to respond quickly to changing business needs.
Operational cost and complexity
Traditional data centers are complex to manage, and GPU machines frequently malfunction. The operation and maintenance team needs to invest a lot of manpower and material resources in daily maintenance and troubleshooting, resulting in high costs and low efficiency.
Computing power bottlenecks limit business innovation
Faced with hundreds or even thousands of GPU cards running simultaneously, network bandwidth performance issues gradually emerged, becoming a major problem hindering computing efficiency.
Poor flexibility and scalability
Faced with rapid market changes, companies find it difficult to quickly adjust computing resources to match new business or project needs, and miss market opportunities.
Advantages
Process Streamlining and Efficiency Improvement
The operation and maintenance process has been significantly optimized, reducing the possibility of manual operations and incorrect configurations. This directly promotes a leap in operation and maintenance work efficiency.
Intelligent Operation and Maintenance
Through data analysis, prediction and early warning, and fault self-healing, the operation and maintenance team can more accurately grasp the system operation status, ensure stable system operation, and solve problems as soon as they occur. This doubles human efficiency.
Flexible Resource Scheduling and Cost Optimization
Relying on resource pools, vGPUs, and fine-grained permission management, the system can flexibly respond to changes in business needs, accurately allocate resources, avoid waste, and significantly reduce operation and maintenance costs.
Flexible Computing and Worry-Free Innovation
Provides a flexible and convenient computing environment that allows algorithm engineers to focus on optimizing and innovating algorithms without being constrained by cumbersome application processes or computing resource limitations.
Accelerated Iteration and Fast Implementation
Full-process optimization ensures smooth transitions from model training to deployment, accelerating project timelines and product launches for algorithm engineers.
Stable Support and Safe Innovation
Multi-node collaboration and efficient scheduling algorithms ensure stable operation of systems under high load, providing a reliable development platform for algorithm engineers.