Processor Configuration API for Workload-Aware Scheduling
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Solution Overview
Problem
Existing job scheduling in data centers often results in inefficient use of computing resources and time due to the lack of consideration of job characteristics, leading to suboptimal processor utilization.
Innovation Solution
A system and method for configuring processors based on job characteristics, using an application programming interface (API) to identify and set processor settings that align with performance preferences, priority, and resource constraints, thereby optimizing workload scheduling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional job scheduling is used without considering job characteristics, then the scheduling process is simple, but computing resource utilization efficiency deteriorates
Solution Approach 1:
The patent applies parameter changes by introducing multiple job characteristic parameters (priority level, performance preference, time constraints, resource requirements) into the scheduling system. The job scheduler evaluates these parameters to dynamically adjust scheduling decisions, transforming the scheduling approach from simple FIFO to a multi-parameter optimization system that improves resource utilization efficiency.
Solution Approach 2:
The scheduling system implements dynamics by making scheduling decisions adaptive rather than static. The job scheduler continuously evaluates job characteristics and processor states, dynamically adjusting which jobs are assigned to which processors based on current system conditions, thereby improving computing resource utilization without requiring overly complex predetermined rules.
2Productivity
If processor settings are not aligned with job requirements, then the system configuration is simple, but job performance deteriorates
Solution Approach 1:
The system applies preliminary action by pre-configuring processor settings according to job requirements before job execution begins. The job scheduler analyzes job characteristics and pre-adjusts processor parameters (such as clock frequency, power states, and resource allocation) to optimize performance from the start of job execution, rather than making adjustments during runtime.
Solution Approach 2:
The patent implements local quality by customizing processor settings specifically for each job's requirements rather than using uniform configuration. Different processors or different cores within processors can be configured with different parameters depending on the specific job characteristics, allowing each processing unit to be optimized locally for its assigned workload.
3Loss of time
If job characteristics are not considered in scheduling, then the scheduling algorithm is simple, but time management efficiency deteriorates
Solution Approach 1:
The scheduling algorithm applies parameter changes by incorporating time-related parameters (time constraints, deadlines, urgency levels) into the scheduling decision-making process. The job scheduler evaluates these temporal parameters alongside other job characteristics to optimize job execution timing, reducing time management inefficiencies without requiring excessively complex scheduling logic.
Data Source
AI summary
Apparatuses, systems, and techniques to perform an application programming interface (API) to identify processor settings to be used when performing one or more software workloads. As an example, one or more processors comprising one or more circuits perform an API to identify processor settings to be used to configure processors assigned to perform a software workload based, at least in part, on one or more characteristics of that software workload.