Memory Timing Sensitivity Analysis for Performance Optimization
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Solution Overview
Problem
Users face challenges in configuring memory system timing parameters to achieve desired performance improvements without risking the memory system's functionality, as numerous parameters interact complexly, leading to unpredictable results and potential system failure.
Innovation Solution
A method and system that automatically identify and predict the sensitivity of memory system performance to timing parameter changes by repeatedly running workloads with varied parameter values, generating performance indications to focus adjustments on critical parameters within safe ranges, and using a prediction module to simulate performance changes without actual component upgrades.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users manually adjust timing parameter values to improve performance, then performance may be improved, but the risk of making the memory system nonfunctional increases
Solution Approach 1:
The system performs preliminary automated testing and analysis of timing parameter sensitivity before users make adjustments. By pre-identifying which parameters are most sensitive and determining safe adjustment ranges, the system enables performance optimization while preventing configurations that would render the memory system nonfunctional.
Solution Approach 2:
The system provides feedback to users about which timing parameters are most sensitive and how changes will affect performance. This feedback mechanism guides users to adjust only the most impactful parameters within safe ranges, improving performance while maintaining system functionality.
2Productivity
If users test multiple timing parameter values to find optimal performance, then performance optimization is possible, but the time and resources required increase significantly
Solution Approach 1:
The system extracts and identifies only the most sensitive timing parameters that have the greatest impact on performance. By focusing testing and optimization efforts on these key parameters rather than all possible parameters, the system achieves effective performance optimization with significantly reduced time and computational resources.
Solution Approach 2:
The system automatically analyzes which timing parameter values produce the best performance and applies those changes without requiring extensive manual testing. By leveraging automated parameter analysis and sensitivity detection, the system finds optimal configurations efficiently.
3Productivity
If users adjust multiple timing parameters simultaneously, then performance improvement potential increases, but predicting the outcome becomes difficult and system stability decreases
Solution Approach 1:
The system segments the complex set of timing parameters into individual components and analyzes their sensitivity and interaction effects separately. By breaking down the complex parameter space into manageable parts and evaluating their individual and combined impacts, the system can predict outcomes of multiple parameter adjustments while maintaining system stability.
Data Source
AI summary
Various timing parameter values for a memory system are changed and a workload is run using the changed timing parameter values resulting in workload performance values. The workload is run multiple times with different timing parameter values and the performance values generated by the workload are used to generate and output a performance indication that identifies how sensitive performance of the physical memory is to the one or more timing parameters. The parameter values generated by the workload are optionally used to predict what parameter value the workload would have generated for user selected timing parameter values (e.g., without running the workload).