If your applications are sensitive to latency and require stable, high-performance resources, use PAI AI computing resources.
Resource types
Cloud-native resources
These resources are primarily used for PAI-DSW, PAI-EAS, and PAI-DLC:
General computing resources
General computing resources, including ECS, ECI, and EGS, provide a flexible, stable, easy-to-use, and high-performance environment for deep learning training. After you activate PAI, the system automatically creates a public resource quota for general computing resources that you can associate with a workspace.
Lingjun resources
Lingjun resources are PAI's computing resources for large-scale deep learning and integrated intelligent computing. Based on hardware-software co-optimization, they provide a high-performance heterogeneous computing foundation. Lingjun resources deliver the high performance, efficiency, and utilization required for high-performance computing. This makes them ideal for development, training, and inference on the PAI platform.
Big data engine resources
These resources are primarily used for PAI-Designer:
MaxCompute
MaxCompute is an enterprise-level Software as a Service (SaaS) cloud data warehouse for data analytics. It provides a fast, fully managed online data warehouse service that eliminates the scalability and elasticity limitations of traditional data platforms. MaxCompute minimizes your O&M costs and lets you process and analyze massive amounts of data cost-effectively. For more information, see What is MaxCompute?.
Fully managed Flink resources
Realtime Compute for Apache Flink is a one-stop, real-time big data analytics platform built on Apache Flink. It offers end-to-end analytics with sub-second latency. For more information, see What is Realtime Compute for Apache Flink?.
Usage
Go to the AI Computing Resources > Resource Pool page to create resource groups of the following types and purchase computing resources:
General computing resources: For details, see Create a resource group and purchase general computing resources.
Lingjun resources: For details, see Create a resource group and purchase Lingjun resources.
Then, create a resource quota on the AI Computing Resources > Resource Quota page for efficient resource allocation and management. You can associate this resource quota with a workspace for AI development and training.
Cloud-native resource quota
After you purchase computing resources in the resource pool, you can allocate the resources from one or more resource groups to one or more resource quotas. You can also create a child quota to form a quota tree for enhanced queuing and scheduling.
Lingjun resources: For details, see Create a resource quota.
General computing resources: For details, see General computing resource quotas.
Big data resource quota
For instructions on activating, purchasing, and using this type of resource quota, see the following topics:
MaxCompute: For details, see MaxCompute resource quotas.
Fully managed Flink resources: For details, see Manage fully managed Flink resources.