Unified Kubernetes Resource Manager for AI Nodes
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Solution Overview
Problem
In AI scenarios, managing diverse resources like GPU, FPGA, ASIC, and InfiniBand within Kubernetes clusters is complex due to the need for multiple components, increasing resource consumption and maintenance complexity.
Innovation Solution
A resource management method that initializes a main process to define and start subprocesses for managing resources, registers them via gRPC service, and allocates resources to containers, reducing the number of system components and maintenance complexity by integrating multiple resource types into a single component.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple components are deployed in each node to manage different resource types (GPU, FPGA, ASIC, InfiniBand), then resource management capability is improved, but system complexity and resource consumption increase
Solution Approach 1:
The patent merges multiple resource management components into a single unified component that can manage multiple resource types (GPU, FPGA, ASIC, InfiniBand) through a common framework. This unified component uses a shared data structure and common management logic to handle different resource types, thereby reducing the number of components deployed per node while maintaining comprehensive resource management capability.
Solution Approach 2:
The unified resource management component is designed with multi-functional capabilities to manage diverse resource types through a single interface. It implements a universal data structure that can represent different resource types and a common management mechanism that handles allocation, monitoring, and coordination for all resource types, making the component adaptable to multiple functions without requiring separate specialized components.
2Adaptability or versatility
If multiple components are deployed in each node to manage different resource types, then resource management capability is improved, but resource consumption increases
Solution Approach 1:
By combining multiple resource management components into one unified component, the patent eliminates redundant processes and operations that would occur with multiple separate components. The unified component shares data structures, management logic, and operational frameworks across different resource types, thereby reducing overall resource consumption including CPU, memory, and energy usage while maintaining the ability to manage multiple resource types.
3Adaptability or versatility
If multiple components are deployed in each node to manage different resource types, then resource management capability is improved, but maintenance complexity increases
Solution Approach 1:
The unified resource management component consolidates multiple management functions into a single deployable unit, which simplifies maintenance operations. Instead of updating, monitoring, and troubleshooting multiple separate components, system administrators only need to manage one unified component. This reduces maintenance complexity while preserving the comprehensive resource management capability across different resource types.
Data Source
AI summary
A resource management method for a node in Kubernetes, a computer device, and a readable storage medium. The method includes following steps: initializing a component to start a main process; defining, by means of the main process, subprocesses for managing resources respectively; in response to a detection from the main process that a plurality of actual resources is present in a node among the resources, starting a subprocess corresponding to each of the actual resources, and starting gRPC service for each started subprocess; and registering the resources corresponding to a subprocesses where the gRPC service is successfully started to Kubernetes by using the main process enabling the subprocesses where the gRPC service is successfully started to manage the actual resources.