Service Queue Capacity Adjustment for Microcode Upgrades
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Solution Overview
Problem
Data processing systems face challenges in minimizing user impact during large data transfers, such as microcode upgrades, which can lead to operating system and application program failures due to timeouts and buffer overflows.
Innovation Solution
Implementing load control logic in adapters to manage service queues, allowing the system to adjust host and service queue loads by limiting subsequent requests during time-critical tasks, thereby ensuring timely completion of large data transfers without delaying other tasks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If the system prioritizes large data transfer operations (such as microcode upgrades), then the data transfer completion time is reduced, but other concurrent operations may experience timeouts and failures
Solution Approach 1:
The patent dynamically adjusts service queue capacity based on operational context. During microcode upgrades, the system reduces service queue capacity to prioritize upgrade operations, while恢复正常 capacity when upgrades are complete. This dynamic adjustment allows the system to optimize for time-critical operations without permanently compromising service availability.
Solution Approach 2:
The system changes the parameter of service queue capacity from a static value to a dynamically adjustable parameter. By modifying queue capacity parameters in response to upgrade operations, the system can control resource allocation to balance between fast data transfer and maintaining service reliability for other operations.
2Productivity
If the service queue capacity is reduced during microcode upgrades, then upgrade operations complete faster, but system resource allocation for other tasks is limited
Solution Approach 1:
The service queue capacity is made dynamic rather than static, allowing the system to adapt resource allocation based on current operational needs. During microcode upgrades, capacity is reduced to accelerate upgrades; during normal operations, capacity is increased to handle diverse workloads, thus maintaining both upgrade productivity and overall system adaptability.
Solution Approach 2:
The system performs preliminary actions by detecting upgrade operations in advance and proactively adjusting service queue capacity before the upgrade completes. This allows the system to prepare resource allocation optimally for the time-critical upgrade operation while minimizing impact on other tasks.
Data Source
AI summary
Systems and methods for adjusting the number of tasks that are accepted for processing in a computer based on processing resources required by the tasks, processing resources available in the computer system, and the time allowed to complete at least one of the tasks. The tasks that are accepted for processing can be scheduled to timeshare the processing resources available so that the task(s) complete within the time allowed.