Timestamp-Indexed Memory Access Record for Adaptive Pool Allocation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing memory management systems face challenges in dynamically optimizing memory allocation among multiple memory pools due to changing workload demands, leading to underutilization or performance issues, as administrators often rely on manual adjustments and oversizing to avoid errors, resulting in suboptimal performance.
Innovation Solution
A system that maintains a timestamp-indexed record of memory access operations to dynamically adjust memory allocation by tracking memory usage over time, migrating record entries, and generating a time-saved array to identify which memory pools benefit most from increased memory, allowing for adaptive reallocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If memory pools are manually optimized based on initial workload analysis, then memory allocation is configured to handle specific workloads, but the optimal allocation changes over time as workload types change, causing underutilization or performance problems
Solution Approach 1:
The patent implements dynamic memory pool optimization by continuously monitoring memory access operations and automatically adjusting memory pool sizes based on observed workload patterns. The system transitions from static manual configuration to dynamic adaptive allocation, where memory pool parameters are adjusted in real-time based on actual usage patterns detected through timestamp-indexed recording of memory access operations.
2Reliability
If administrators oversize memory pools to handle worst-case scenarios, then system errors are avoided and the need for reallocation is reduced, but significant performance loss occurs for other memory pools
Solution Approach 1:
The patent enables memory pools to self-optimize by automatically monitoring their own access patterns and adjusting their sizes based on observed workload characteristics. Each memory pool can independently track its usage through timestamp-indexed records and participate in automated optimization decisions, eliminating the need for administrators to manually oversize pools as a safety margin.
Solution Approach 2:
The system implements feedback mechanisms by continuously recording memory access operations with timestamps and using this data to inform optimization decisions. The timestamp-indexed record provides feedback about actual memory usage patterns, enabling the system to adjust pool sizes based on empirical evidence rather than worst-case assumptions.
3Ease of manufacture
If administrators manually adjust memory allocation parameters, then initial optimization is achieved, but administrators typically do not revisit these parameters causing pools to become underutilized
Solution Approach 1:
The patent transforms memory pool optimization from a manual administrative task into an automated self-service process. The system automatically monitors memory access patterns, analyzes workload characteristics, and adjusts memory pool parameters without requiring administrator intervention. This continuous automated optimization ensures memory pools remain efficiently sized as workloads evolve.
Data Source
AI summary
A memory management system determines a timestamp for a memory access operation that accesses a block of data, and uses the timestamp to access a timestamp-indexed record. The timestamp-indexed record includes a plurality of record arrays, each of which corresponds to a different time range, and includes one or more record entries of a different array-specific time duration. The system selects a record entry that indicates a time range associated with the timestamp, and that indicates an amount of memory accessed during the indicated time range. The system then updates the selected record entry to account for the memory size of the block of data.