Background
Batch AI processing (e.g., document analysis, image recognition, etc.) tends to be resource-intensive, especially when the tasks are unevenly distributed and can become idle or overloaded.
optimization strategy
- Reasonable time windows:: Off-peak execution of batch processing to enjoy lower resource prices based on task flexibility
- Using Task Grouping: Batch submission of similar tasks to improve processing efficiency
- Dynamic resource allocation: Utilize the platform's adaptive reasoning capabilities to allow the system to automatically adjust resource allocation
- Results Cache: For repetitive queries, consider caching results to avoid double counting
best practice
It is recommended to review the execution logs of batch tasks on a regular basis to analyze the resource usage patterns and continuously optimize the task scheduling strategy.Kluster.ai's task management interface provides sophisticated monitoring features to support this process.
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