Heterogeneous Workload Placement via Core Metrics
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Solution Overview
Problem
Cloud datacenters face inefficiencies in processing core workload assignment due to varying performance characteristics of processing cores based on different instruction set architectures (ISAs), which can lead to suboptimal execution times and resource utilization.
Innovation Solution
A method and apparatus that assign processing core workloads to the most suitable ISA-based processing cores within a heterogeneous ISA pool based on obtained processing core metrics, such as bootup times, execution rates, and memory page sizes, ensuring critical workloads are executed on the fastest or most efficient cores.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If processing cores based on different ISAs are used in datacenters, then hardware versatility and resource utilization are improved, but performance consistency and workload assignment accuracy deteriorate due to varying performance characteristics
Solution Approach 1:
The system changes the parameter of workload assignment criteria from generic to specific. Instead of treating all processing cores uniformly, the system modifies assignment parameters based on ISA type, performance metrics, and workload characteristics to achieve both versatility and performance consistency.
Solution Approach 2:
The patent replaces manual or heuristic workload assignment mechanisms with an automated metric-based selection system. The system substitutes traditional load balancing approaches with a quantitative evaluation framework that uses performance metrics to objectively select optimal processing cores.
2Loss of time
If critical workloads are assigned to fastest processing cores, then execution time is improved, but resource allocation complexity increases
Solution Approach 1:
The system implements feedback mechanisms by continuously monitoring performance metrics of processing cores and adjusting workload assignments accordingly. This feedback loop enables the system to automatically optimize resource allocation without manual intervention, reducing complexity despite the sophisticated assignment strategy.
Solution Approach 2:
The system performs preliminary actions by pre-evaluating and ranking processing cores based on their performance characteristics before workload assignment. This preliminary sorting and classification allows the system to quickly assign critical workloads to the most suitable cores without complex real-time calculations.
3Productivity
If heterogeneous ISA processing cores are deployed, then processing capability and adaptability are improved, but workload placement accuracy and execution efficiency deteriorate due to varying memory architectures and performance characteristics
Solution Approach 1:
The system applies local quality by tailoring workload placement decisions to the specific characteristics of each processing core. Instead of uniform treatment, the system adjusts placement strategies based on local factors such as ISA type, memory architecture, and performance metrics to achieve both high processing capability and accurate workload placement.
Solution Approach 2:
The patent introduces an intermediary workload placement system that mediates between workload requirements and processing core capabilities. This intermediary layer analyzes both sides and facilitates optimal matching, resolving the complexity introduced by heterogeneous ISAs and improving placement accuracy.
Data Source
AI summary
The methods and apparatus can assign processing core workloads to processing cores from a heterogeneous instruction set architectures (ISA) pool of available processing cores based on processing core metric results. For example, the method and apparatus can obtain processing core metric results for one or more processing cores, such as processing cores within general purpose processors, from a heterogeneous ISA pool of available processing cores. The method and apparatus can also obtain one or more processing core workloads, such as software applications or software processes, from a pool of available processing core workloads to be assigned. The method and apparatus can then assign one or more processing core workloads that have higher priority than others from the pool of available processing core workloads to a processing core from the heterogeneous ISA pool of available processing cores based on its processing core metric result.