Job Management System for Machine Learning Cluster Experiment Control
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Solution Overview
Problem
In machine learning, managing and controlling the execution of jobs in a computer cluster system is challenging due to the complexity of hyperparameters and the need for efficient tracking and updating of experiment information during job execution.
Innovation Solution
A method and system that record and update job information and experiment information, including mapping experiment information to job identifiers, allowing for control of job execution by transmitting changes in experiment information to the computer cluster system, enabling features like interrupting, resuming, or updating job parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If experiment information is recorded and mapped to job identifiers for tracking machine learning experiments, then measurement precision and information completeness are improved, but device complexity and data management burden increase
Solution Approach 1:
The patent introduces an intermediary component (experiment information recording module) that acts as a mediator between the job execution system and the experiment data. This module maps experiment information to job identifiers and stores them in a structured manner, reducing the complexity burden on the core execution system while maintaining precise tracking capabilities.
Solution Approach 2:
The system segments experiment information into distinct components (job identifiers, parameter information, measurement information, resource information) that can be independently managed and mapped. This segmentation allows for organized storage and retrieval without overwhelming the system with monolithic data structures.
2Adaptability or versatility
If job execution control is implemented by transmitting changes in experiment information to the computer cluster system, then adaptability and control capability are improved, but communication overhead and system response time increase
Solution Approach 1:
The system performs preliminary actions by pre-mapping experiment information to job identifiers and maintaining a structured repository of experiment data before execution changes are needed. When control actions are required, the system can quickly retrieve and transmit only the necessary changes rather than processing entire data sets, reducing communication overhead.
Solution Approach 2:
The patent extracts only the essential control-relevant information from the comprehensive experiment data and transmits it to the computer cluster system. By taking out only the necessary parameters and changes needed for job execution control, the system maintains adaptability while minimizing communication time and bandwidth usage.
3Loss of information
If comprehensive job information and experiment information are recorded and mapped, then information completeness is improved, but data processing time and storage requirements increase
Solution Approach 1:
The patent segments comprehensive information into distinct categories (job identifiers, parameter information, measurement information, resource information, time information) and maps them to corresponding job identifiers. This segmentation enables efficient indexing and retrieval, allowing the system to maintain complete information while reducing processing time by accessing only relevant segments when needed.
Solution Approach 2:
The system adds a dimensional organization to the stored information by creating mappings between experiment information and job identifiers across multiple dimensions (experiment ID, job ID, parameter types, time stamps). This multi-dimensional organization allows for efficient queries and retrieval operations without requiring linear processing of all data.
Data Source
AI summary
A method of a system including a processor including recording experiment information of a job in connection with job information generated based on an execution of a job of a computer cluster system, and controlling further execution of a job, by the computer cluster system, by transmitting a change in the experiment information to the computer cluster system based on the job information.