Environmental Signatures for Hardware Test Scheduling
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Solution Overview
Problem
Current test scheduling methods in hardware testing environments fail to accurately manage power and temperature usage, leading to inefficiencies and potential resource constraints, as they do not account for specific workload behaviors, resulting in suboptimal scheduling that may cause spikes in both temperature and power consumption.
Innovation Solution
A method and system that generate environmental signatures based on power and temperature usage of hardware components during testing, combined with an outcome score, to optimize test scheduling and resource management, allowing for better decision-making on test prioritization and resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If tests are scheduled based on manufacturer specifications for heat and power usage, then the scheduling process is simple and fast, but the accuracy of environmental impact assessment is poor
Solution Approach 1:
The system performs preliminary actions by generating environmental signatures for each test case in advance, capturing their power and temperature characteristics before actual test execution. This allows the scheduling system to make informed decisions based on pre-analyzed environmental data rather than manufacturer specifications, improving accuracy while maintaining operational simplicity during test execution.
Solution Approach 2:
The system creates copies of environmental characteristics by generating environmental signatures that represent the actual power and temperature behavior of tests. These signatures serve as accurate replicas of environmental impact, replacing the need for complex real-time monitoring and manual assessment, thus improving measurement precision without proportionally increasing system complexity.
2Productivity
If automated test scheduling is implemented without environmental considerations, then test execution efficiency is high, but temperature and power usage spikes occur
Solution Approach 1:
The system implements feedback by using environmental signatures to inform scheduling decisions. The scheduler continuously references the environmental characteristics of pending tests and adjusts the test sequence to avoid combining tests with similar high power or temperature profiles, thereby maintaining stable environmental conditions while preserving test execution efficiency.
Solution Approach 2:
The scheduling system dynamically adjusts test sequences based on environmental signatures rather than following a static schedule. It adapts the test execution order to balance environmental impact, selecting tests that complement each other in terms of power and temperature characteristics, thus preventing spikes while maintaining high productivity.
3Productivity
If multiple tests with high environmental impact are scheduled together, then test throughput is maximized, but resource constraints are violated
Solution Approach 1:
The system uses environmental signatures as feedback to evaluate whether scheduling multiple high-impact tests together would violate resource constraints. Before finalizing a test schedule, the system checks the cumulative environmental impact against available resources, ensuring compliance while still maximizing throughput by optimizing the mix of tests.
Solution Approach 2:
The system changes scheduling parameters by incorporating environmental signature data into the scheduling algorithm. This allows the system to dynamically adjust which tests are grouped together based on their environmental characteristics, ensuring that resource constraints are respected while maintaining high test throughput through intelligent parameter optimization.
4Productivity
If environmental monitoring is added to test scheduling, then environmental optimization is achieved, but system complexity and overhead increase
Solution Approach 1:
The system performs environmental characterization in advance by generating signatures during test development or initial runs. This preliminary action captures all necessary environmental data without requiring complex real-time monitoring infrastructure during actual test execution, thus achieving resource optimization while minimizing added system complexity.
Solution Approach 2:
The system uses environmental signatures as simplified copies of the actual environmental behavior. These signatures capture the essential power and temperature characteristics without requiring continuous complex monitoring, enabling efficient resource utilization decisions while keeping the monitoring and control system relatively simple.
Data Source
AI summary
Method and system are provided for using environmental signatures for test scheduling. The method includes: generating an environmental signature for a test including the usage of power and temperature of one or more hardware components being tested; determining an outcome score of the test; and scheduling one or more tests on hardware components based on the environmental signature and outcome score of candidate tests. Generating an environmental signature for a test may include: monitoring the usage of power by hardware components during the course of the test; monitoring the temperature of hardware components during the course of the test; generating a signature representing the power usage and temperature during the test. Determining an outcome score of the test may include determining the number of defects exposed by a test and basing the outcome score on the number of defects exposed.