Memory Compression Lookup Tables for Faster Address Translation
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Solution Overview
Problem
Existing memory compression techniques face challenges with high latency and bandwidth overhead due to computationally-intensive compression and decompression operations, fragmented memory utilization, and inefficient lookup table caching, which affects access times and memory efficiency.
Innovation Solution
Implementing an improved lookup table scheme that uses partitioned memory with configurable compression ratios and partition identifiers, reducing the size of the lookup table by storing identifiers instead of full addresses, and utilizing a cache-friendly structure for address translation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional lookup table caching is used for address translation in memory compression, then address translation can be performed, but the lookup table size becomes large and cache hit rates decrease
Solution Approach 1:
The patent divides the memory address space into multiple segments or partitions, each with its own compressed lookup table. Instead of maintaining one large lookup table for the entire address space, the system creates smaller, manageable segments that can be cached more effectively. This segmentation reduces the size of individual lookup tables while maintaining complete address translation coverage across all memory regions.
Solution Approach 2:
The patent introduces a hierarchical dimension to the lookup table structure by organizing addresses into multiple levels of abstraction. The first level identifies the memory segment or partition, and subsequent levels provide detailed address translation within that segment. This multi-dimensional organization allows the system to cache only the most frequently accessed segments in high-speed cache memory while storing less frequently accessed segments in slower memory.
2Quantity of substance
If compression and decompression operations are performed on all data, then memory utilization increases, but latency and bandwidth overhead increase due to computationally-intensive operations
Solution Approach 1:
The patent applies compression selectively rather than uniformly across all data. The system analyzes local data characteristics and applies compression only to data regions that exhibit compressibility patterns. Hot data or data with poor compression ratios are left uncompressed, while cold data or highly compressible data undergo compression. This local quality approach ensures that compression benefits are realized only where appropriate, avoiding unnecessary computational overhead.
Solution Approach 2:
The patent dynamically adjusts compression parameters such as compression ratio, block size, and algorithm selection based on data characteristics and system conditions. The system monitors compression effectiveness and latency metrics, then adapts compression parameters to optimize the balance between memory utilization and access speed. This parameter adjustment allows the system to achieve high memory utilization during periods of low activity while maintaining acceptable latency during high-performance requirements.
3Measurement precision
If full addresses are stored in the lookup table for address translation, then complete address mapping is achieved, but the lookup table size increases and memory efficiency decreases
Solution Approach 1:
The patent extracts only the essential components needed for address translation from the full address structure. Instead of storing complete source and destination addresses in the lookup table, the system extracts and stores only the critical segment identifiers and offset information. The full address translation is reconstructed by combining these extracted components with the base address information, achieving complete address mapping while using minimal lookup table space.
Data Source
AI summary
A system can include a memory; and a processing device, operatively coupled with the memory, to perform operations including: partitioning the memory into a plurality of memory partitions, wherein each of the plurality of memory partitions is associated with a corresponding partition identifier; receiving a host command to access data; identifying a compression ratio of the data; identifying a memory partition among the plurality of memory partitions; identifying a location among a plurality of locations on the memory partition by using a segment identifier and a unit offset address, wherein each of the plurality of locations is associated with a corresponding segment identifier, and wherein the unit offset address is determined in view of a compression ratio range associated with the memory partition; and performing an operation regarding the data at the identified location on the memory partition.