Distributed Workload Scheduling With Dynamic Communication Workgroups
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Solution Overview
Problem
Computing devices face limitations in efficiently managing workloads due to constrained computing resources and inefficient communication protocols, leading to bottlenecks in workload performance.
Innovation Solution
A workload management framework that dynamically configures communication elements based on workload requirements, forming workgroups and adjusting communication protocols to optimize performance, using intent queues and consensus-based leader election systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If computing devices use conventional communication protocols and static resource allocation, then system simplicity is maintained, but workload performance efficiency deteriorates due to bottlenecks
Solution Approach 1:
The patent implements dynamic configuration of communication elements that adapt based on workload requirements. The system transitions from static communication protocols to dynamic ones that can be reconfigured in real-time based on the specific needs of different workloads, thereby improving efficiency without requiring completely new communication infrastructure.
Solution Approach 2:
The patent segments the distributed system into workgroups that can be independently configured and managed. Each workgroup can have its own optimized communication protocol configuration, allowing different parts of the system to operate with different levels of complexity appropriate to their specific workload requirements.
2Productivity
If computing devices allocate more computing resources to handle workloads, then workload processing capacity is improved, but resource utilization efficiency deteriorates due to constrained and inefficient allocation
Solution Approach 1:
The patent implements a feedback mechanism where the system continuously monitors workload progress and resource availability, then dynamically adjusts resource allocation accordingly. This ensures that computing resources are allocated efficiently based on actual needs rather than static pre-allocation, improving both capacity and utilization efficiency.
Solution Approach 2:
The patent creates a framework where communication elements can serve multiple workgroups with different requirements. The same communication infrastructure is universally applied but dynamically configured for different workloads, eliminating the need for dedicated resources for each workload type and improving overall utilization efficiency.
3Ease of operation
If computing devices establish fixed workgroups for workload performance, then coordination overhead is reduced, but adaptability to changing workload requirements deteriorates
Solution Approach 1:
The patent implements dynamic workgroup configuration where workgroups can be created, modified, or dissolved based on workload requirements. The system maintains the coordination benefits of fixed workgroups during execution while allowing dynamic reconfiguration between workloads, achieving both ease of operation during execution and adaptability to changing requirements.
Data Source
AI summary
Methods and systems for performing workloads are disclosed. The workloads may be distributed across any number of processing elements for performance. The processing elements may be supported by communication elements. The operation of the communication elements may impact the rate at which the processing elements are able to complete the workloads. The operation of the communication elements may be dynamically configured to speed completion of workloads.