Intelligent Storage Architecture Dynamic Hardware Configuration
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Solution Overview
Problem
Current computing systems face challenges in dynamically configuring hardware to optimize performance, power, endurance, scalability, and cost due to the need for a single configuration setting that may not adapt well to varying application requirements and business priorities, leading to sub-optimal results.
Innovation Solution
An Infrastructure Description Language (IDL) is used to provide Service Level Hints (SLHs) and Service Level Requirements (SLRs) that a master controller employs to dynamically configure hardware components, allowing for trade-offs between performance, power, endurance, and cost based on application characteristics and business needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by stationary object
If a single hardware configuration is set by an administrator to optimize energy cost, then energy consumption is reduced, but performance capability is sacrificed
Solution Approach 1:
The hardware configuration is made dynamic through runtime reconfiguration capabilities. The system can switch between different configuration states (e.g., performance-optimized vs. energy-optimized modes) based on current workload characteristics and service level requirements, rather than being fixed to a single static configuration.
Solution Approach 2:
The invention changes hardware parameters dynamically at runtime based on application characteristics and service level hints. Configuration parameters such as cache sizes, buffer allocations, and processing priorities can be adjusted to match current performance needs while managing energy consumption appropriately.
2Productivity
If hardware is configured to maximize performance for all operations, then performance capability is improved, but energy cost increases
Solution Approach 1:
Different parts of the hardware system are configured with different quality levels based on local needs. Critical performance paths receive optimized configurations while less critical functions use energy-efficient configurations, allowing selective application of performance optimization rather than system-wide maximization.
Solution Approach 2:
The system applies performance optimization partially and selectively based on service level requirements. Rather than maximizing performance everywhere, the system applies optimization only where and when needed according to application characteristics and business priorities, avoiding excessive energy consumption in non-critical areas.
3Stability of the object's composition
If a single configuration setting is used for extended periods, then configuration stability is maintained, but adaptability to varying application requirements deteriorates
Solution Approach 1:
The configuration system transitions from static to dynamic, enabling runtime adaptation while maintaining stability through controlled reconfiguration. The system can adjust configuration parameters in response to changing application characteristics without requiring complete reconfiguration, thus balancing stability and adaptability.
Solution Approach 2:
The system incorporates feedback mechanisms that monitor application characteristics, workload patterns, and performance metrics to automatically adjust configuration settings. This closed-loop approach maintains configuration stability by making incremental, informed adjustments rather than frequent radical changes, adapting to varying requirements while preserving system stability.
Data Source
AI summary
An Infrastructure Description Language (IDL) includes Service Level Hints (SLHs) and Service Level Requirements (SLRs). The SLHs and SLRs are used to configure at least one hardware resource in a computing system having an intelligent configurator to broker a hardware configuration based on the SLHs and SLRs.