Memory Access Pattern Recognition for Adaptive Cache Prefetching
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Solution Overview
Problem
Existing memory access technologies face challenges in efficiently predicting and prefetching data due to the overhead of offline-generated heat maps and latency differences between volatile and non-volatile storage mediums, leading to suboptimal cache performance.
Innovation Solution
A two-level clustering model is employed to group physical memory addresses, monitoring active regions for repeated jump patterns to predict next memory addresses and prefetch data from non-volatile storage to cache memory, using a pattern recognition algorithm to improve hit rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If offline-generated heat maps are used for memory access prediction, then prediction capability is provided, but system overhead and complexity increase
Solution Approach 1:
The memory device performs pattern recognition and prediction autonomously using its own processor and storage resources, without requiring external offline heat map generation. The device monitors its own access patterns and generates predictions internally, eliminating the overhead of external prediction systems while maintaining reliable prediction capability
Solution Approach 2:
The patent extracts only the essential prediction functionality needed for operation, implementing a streamlined pattern recognition system that identifies access patterns and generates predictions without the full complexity of offline heat map generation and maintenance. This selective extraction reduces system overhead while preserving core prediction benefits
2Productivity
If data is prefetched from non-volatile storage to cache memory, then cache performance improves, but latency differences between storage mediums create inefficiency
Solution Approach 1:
The system performs preliminary pattern recognition to identify future memory access addresses before they are actually needed. By detecting access patterns and predicting next access points in advance, the system can initiate prefetching operations proactively, reducing the perceived latency by having data ready before it is requested
Solution Approach 2:
The patent implements dynamic pattern recognition that adapts to changing access patterns in real-time. The system continuously monitors access behavior and adjusts its predictions dynamically, allowing it to optimize prefetching timing and reduce latency by responding to actual runtime behavior rather than static pre-configured parameters
3Measurement precision
If pattern recognition algorithms monitor multiple distances and criteria, then prediction accuracy improves, but processing complexity increases
Solution Approach 1:
The patent segments the pattern recognition process into distinct stages: identifying first distances between accessed addresses, then identifying second distances based on first distances that meet criteria, and finally generating predictions based on second distances. This segmentation allows the system to process multiple criteria systematically without overwhelming complexity, improving accuracy through structured analysis
Solution Approach 2:
The system implements a multi-criteria approach where it first identifies distances that meet a first criterion, then among those, identifies distances that meet a second criterion. This partial action approach processes data in manageable waves, achieving high prediction accuracy through multiple filtering stages while controlling processing complexity by only advancing to the next stage when previous criteria are satisfied
Data Source
AI summary
Systems and methods for pattern recognition are described. A storage device may include a first storage medium; a processor configured to: identify a first distance between first memory addresses accessed by a computing device that satisfies a first criterion; based on identifying the first distance that satisfies the first criterion, identify a second distance between second memory addresses accessed by the computing device that satisfies a second criterion; based on identifying the second distance that satisfies the second criterion, detect a pattern including the first distance and the second distance; and retrieve from the first storage medium, based on the pattern, data associated with a third memory address.