Storage Adapter Controller Resource Pool Allocation
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Solution Overview
Problem
Storage adapters often act as a performance bottleneck in computer systems, particularly with the increasing popularity of solid state drives (SSDs), necessitating a method and controller for optimizing storage adapter performance while maintaining efficient functions such as Write Caching and RAID operations.
Innovation Solution
A controller with multiple hardware engines and resource pools, utilizing a processor to initialize allocation types and maintain page counts for deadlock avoidance, and employing checking functions to manage work queues and allocate resources efficiently, minimizing hardware and firmware interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional storage adapter resource allocation is used, then basic storage functions are maintained, but I/O operation time is excessive and performance is bottlenecked
Solution Approach 1:
The patent segments storage resources into multiple resource pools (cache pools, buffer pools, I/O operation pools) and divides work into separate work queues. This segmentation allows parallel processing of different I/O operations and prevents single-threaded bottlenecks, directly improving I/O operation speed and reducing operation time.
Solution Approach 2:
The patent implements dynamic resource allocation where the controller automatically assigns resources from appropriate pools based on the type and requirements of each I/O operation. This dynamic allocation optimizes resource utilization in real-time, enhancing productivity while minimizing idle time and wait states.
2Loss of time
If resource allocation is optimized for speed, then I/O operation time is reduced, but system stability and deadlock avoidance become problematic
Solution Approach 1:
The patent establishes water mark thresholds (high water marks and low water marks) for each resource pool before operations begin. These pre-set thresholds guide resource allocation decisions and prevent over-allocation that could lead to deadlocks. By planning resource usage in advance within safe boundaries, the system maintains both speed and stability.
Solution Approach 2:
The patent continuously monitors resource pool status and adjusts allocation based on feedback from water mark comparisons. When resources approach critical levels, the system automatically adjusts allocation to prevent deadlock conditions. This closed-loop control ensures reliable operation while maintaining optimized performance.
3Productivity
If multiple resource pools and work queues are implemented, then I/O operation time is reduced, but device complexity increases
Solution Approach 1:
The patent designs resource pools and work queues with universal structures that can handle multiple types of I/O operations (read, write, delete, etc.) through a unified allocation mechanism. This multi-functionality reduces the need for separate specialized structures for each operation type, managing complexity while maintaining high productivity.
4Productivity
If hardware engines and checking functions are added, then resource allocation efficiency is improved, but hardware-firmware interaction overhead increases
Solution Approach 1:
The patent implements self-service mechanisms where hardware engines autonomously perform allocation checks against water marks and automatically select appropriate resource pools without constant firmware intervention. This reduces hardware-firmware interaction overhead while maintaining efficient resource allocation through built-in decision logic.
Data Source
AI summary
A method and controller for implementing storage adapter performance optimization with enhanced resource pool allocation, and a design structure on which the subject controller circuit resides are provided. The controller includes a plurality of hardware engines; a processor, and a plurality of resource pools. A plurality of work queues is associated with the resource pools. The processor initializes a list of types, and the associated amount of pages for each allocate type. The hardware engines maintain a count of allocate types, specifying a type on each allocation and deallocation, and performing allocation from the resource pools for deadlock avoidance.