Task Dispatch Server for Cloud Resource Pool Segmentation
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Solution Overview
Problem
Cloud server technologies face inefficiencies in dynamically allocating computing resources between CPU-only and co-processor-equipped platforms for task execution, leading to suboptimal resource utilization and task processing.
Innovation Solution
A cloud service system with two parallel resource pools, one without co-processors and the other with, is managed by a task dispatch server that checks task attributes to efficiently route tasks to the appropriate pool based on resource requirements, utilizing co-processors when needed and CPU-only resources when not.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If computing resources are consolidated into a single pool without differentiation, then device complexity is reduced, but resource utilization efficiency deteriorates due to inability to match specific task requirements
Solution Approach 1:
The computing resource pool is segmented into multiple pools based on hardware characteristics: CPU-only pools, GPU pools, NPU pools, and other co-processor pools. This segmentation allows the task dispatch server to match tasks with appropriate resource types, improving resource utilization efficiency while maintaining manageable system complexity through structured organization.
2Productivity
If computing resources are differentiated into multiple pools with co-processors, then resource utilization efficiency is improved through better task matching, but device complexity increases due to multiple resource pools
Solution Approach 1:
The task dispatch server acts as an intermediary between tasks and computing resource pools. It checks task attributes (such as whether co-processor is required) and automatically routes tasks to appropriate pools, thereby managing the complexity of multiple resource pools through centralized intelligent dispatch rather than requiring complex direct mappings.
3Speed
If tasks are dispatched without checking task attributes, then dispatch speed is maintained, but task execution efficiency deteriorates due to mismatched resource allocation
Solution Approach 1:
The task dispatch server performs preliminary checking of task attributes (such as co-processor requirements) before dispatching tasks. This preliminary action ensures that tasks are routed to appropriate computing resource pools in advance, improving task execution efficiency while maintaining dispatch speed through streamlined attribute checking procedures.
Data Source
AI summary
A cloud service system and an operation method thereof are provided. The cloud service system includes a first computing resource pool, a second computing resource pool, and a task dispatch server. Each computing platform in the first computing resource pool does not have a co-processor. Each computing platform in the second computing resource pool has at least one co-processor. The task dispatch server is configured to receive a plurality of tasks. The task dispatch server checks a task attribute of a task to be dispatched currently among the tacks. The task dispatch server chooses to dispatch the task to be dispatched currently to the first computing resource pool or to the second computing resource pool for execution according to the task attribute.