Memory Region Identification for Low-Overhead Data Prefetching
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Solution Overview
Problem
Existing memory systems face challenges in efficiently prefetching data due to the overhead of translating offline-generated heat maps to physical addresses at runtime, leading to inefficiencies in accessing volatile and non-volatile storage media.
Innovation Solution
A two-level clustering model is employed to adaptively group physical memory addresses, monitoring active regions for prefetching decisions, using a hot region recommender to identify and promote sub-regions as hot regions based on access patterns, and periodically evaluating these regions to optimize data prefetching.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If offline-generated heat maps are translated to physical addresses at runtime, then prefetching decisions can be made, but translation overhead reduces system efficiency
Solution Approach 1:
The system pre-processes and stores the mapping between heat map regions and physical memory regions in advance, so that at runtime only simple region matching is needed rather than full address translation. This preliminary preparation eliminates the translation overhead while preserving prefetching accuracy.
Solution Approach 2:
The patent introduces an intermediary data structure (region mapping table) that bridges the offline heat map data and the physical memory addresses. This intermediary pre-computes and stores the correspondence relationships, allowing the runtime system to make prefetching decisions without performing expensive address translations.
2Productivity
If data is prefetched from non-volatile storage to cache memory, then cache hit rate improves, but memory access complexity increases
Solution Approach 1:
The patent divides the memory system into distinct regions (hot regions, cold regions, frequently accessed regions, infrequently accessed regions) and applies different prefetching strategies to each segment. This segmentation simplifies the access complexity by treating different regions differently, while improving cache hit rate by prefetching only from regions that benefit from it.
Solution Approach 2:
The system applies prefetching selectively based on local characteristics of memory regions rather than uniformly across all memory. By identifying hot regions through the two-level clustering model and applying prefetching only to those regions, the system improves cache hit rate while avoiding the complexity overhead of prefetching from all memory locations.
3Productivity
If two-level clustering model is used to group memory addresses, then prefetching efficiency improves, but computational overhead increases
Solution Approach 1:
The patent implements a dynamic two-level clustering model where clusters are formed and updated based on runtime access patterns. The system adapts the clustering structure dynamically, merging or splitting clusters as access patterns evolve, which improves prefetching efficiency while managing computational overhead through adaptive rather than static analysis.
Solution Approach 2:
The system performs clustering analysis periodically rather than continuously, evaluating memory access patterns at scheduled intervals to update the two-level cluster structure. This periodic approach maintains prefetching efficiency by keeping clusters current while reducing computational overhead by avoiding constant re-analysis of access patterns.
Data Source
AI summary
Systems and methods for identifying regions of a memory device are disclosed. A storage device comprises a first storage medium, a second storage medium, and a processor configured to: identify a first memory address; identify a first region of the first storage medium based on the first memory address; identify a first criterion associated with the first memory address; based on identification of the first criterion, identify a portion of the first region based on the first memory address; identify a second criterion associated with the portion; and retrieve data associated with the portion from the first storage medium to the second storage medium based on identification of the second criterion.