Thread Latency Analysis via Preemption and Run-Queue Metrics
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Solution Overview
Problem
Thread latency occurs due to unintentional starvation of threads for access to resources, leading to performance bottlenecks in multi-processor systems, as existing methods fail to effectively analyze and address the factors contributing to this latency.
Innovation Solution
A method and apparatus that collect and analyze statistical data on thread in-run-queue time and preempted time to evaluate thread latency, allowing for identification of preemption and power management-related issues, and provide insights for optimizing thread priority assignment and power management policies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If threads are scheduled based on priority in a multi-processor system, then resource allocation efficiency is improved, but thread latency increases due to unintentional starvation and preemption
Solution Approach 1:
The patent implements a feedback mechanism by collecting statistical data on thread preemption and run-queue times, then using this information to evaluate and adjust scheduling decisions. The system monitors thread latency metrics and feeds this information back to the scheduler to optimize resource allocation while reducing thread starvation and latency
Solution Approach 2:
The patent replaces traditional priority-based scheduling mechanisms with a data-driven evaluation system that uses statistical analysis of thread behavior patterns. Instead of relying solely on static priority assignments, the system substitutes mechanical scheduling with intelligent decision-making based on collected performance data
2Use of energy by moving object
If power management policies are applied to hardware resources, then energy consumption is reduced, but thread execution time increases due to preemption and resource availability issues
Solution Approach 1:
The patent applies dynamic adjustment to power management policies by continuously monitoring thread execution patterns and adapting resource allocation in real-time. The system dynamically balances power savings with execution time requirements by adjusting CPU frequency, voltage, and resource allocation based on current workload characteristics and thread priorities
Solution Approach 2:
The patent changes power management parameters such as CPU frequency, voltage levels, and resource allocation settings based on analyzed thread latency data. By adjusting these parameters dynamically according to actual thread behavior patterns, the system optimizes both energy efficiency and execution performance
3Productivity
If statistical data collection is implemented to analyze thread behavior, then system performance optimization is enabled, but computational overhead increases
Solution Approach 1:
The patent implements partial data collection by focusing only on critical thread metrics such as preemption events and run-queue times, rather than collecting complete traces of all thread activities. This selective approach provides sufficient information for performance optimization while minimizing the computational overhead of data collection and processing
Data Source
AI summary
A method for analysis of thread latency includes: determining a thread of interest; computing a summation of time periods in which the thread of interest stays in a run queue to determine a thread in-run-queue time; computing a summation of time periods in which the thread of interest is preempted by other threads to determine a thread preempted time; and evaluating thread latency of the thread of interest according to the thread preempted time to the thread in-run-queue time.