Multi-Level Hashing System for Cache Collision Resolution
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Solution Overview
Problem
Cache systems face inefficiencies due to high probabilities of hash collisions, leading to delays and cache misses, as traditional hash functions are time-consuming and prone to accidental deletion of important data, especially when the cache is nearly full.
Innovation Solution
Implementing a multi-level hashing system with different-sized hash tables using prime and integer-based hash functions, where each successive layer reduces hash collision probabilities, and a content-addressable memory (CAM) is used to store collided entries, ensuring constant access time and low failure probability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a traditional hash function is used in the cache, then the cache can store and retrieve data, but hash collisions occur frequently causing delays and cache misses
Solution Approach 1:
The patent divides a single hash table into multiple hash tables (first hash table, second hash table, etc.), each handling different portions of the data. When a collision occurs in one hash table, the system segments the resolution process by attempting to store the data in subsequent hash tables, thereby distributing the collision load and maintaining cache performance.
Solution Approach 2:
The patent introduces an intermediary content-addressable memory (CAM) between the hash tables and the final storage location. The CAM acts as a mediator that can resolve collisions by providing alternative storage paths, reducing the impact of hash collisions on cache hit rate and access time.
2Quantity of substance
If the cache is filled to increase storage capacity, then more data can be cached, but hash collision probability increases significantly
Solution Approach 1:
By segmenting the cache into multiple hash tables, the patent allows the cache to maintain high capacity while distributing entries across multiple tables. This segmentation ensures that even as total cache capacity increases, the probability of collision in any single table remains manageable, as collisions can be resolved by attempting storage in subsequent tables.
Solution Approach 2:
The patent adds an additional dimension to the hash table structure by introducing multiple hash tables in sequence rather than relying on a single table. This dimensional expansion allows the system to accommodate more data while providing multiple pathways for collision resolution, effectively reducing collision probability even at high cache utilization.
3Reliability
If multiple hash tables are implemented to reduce collisions, then collision probability decreases, but system complexity increases
Solution Approach 1:
The patent divides the hashing function into multiple segments (first hash function, second hash function, etc.), each corresponding to a separate hash table. This segmentation allows the system to reduce collision probability through the combined effect of multiple tables while keeping each individual table relatively simple in structure.
Solution Approach 2:
The patent implements a partial multi-table approach where only the necessary number of hash tables are used to achieve acceptable collision rates. The system does not require all possible hash tables to be fully utilized, allowing for a balance between collision reduction and system complexity by using just enough tables to achieve the desired performance.
4Quantity of substance
If hash functions are performed frequently to handle collisions, then data can be stored despite collisions, but processing time increases
Solution Approach 1:
The patent performs preliminary hashing by computing hash values for multiple tables in advance or in parallel rather than sequentially. By preparing the hashing structure beforehand and using the CAM to pre-resolve potential collisions, the system reduces the actual processing time required when storing data, even though multiple hash functions are involved.
Solution Approach 2:
The CAM serves as an intermediary that can quickly determine whether a collision will occur before full hash function execution is required. This preliminary check by the CAM allows the system to avoid executing multiple complete hash functions in cases where the CAM can resolve the situation, thereby reducing overall processing time while maintaining data storage capability.
Data Source
AI summary
Computer circuitry is provided for fast caching, which includes a memory, a processor, and a cache. The memory stores a data block. The processor retrieves the data block from the memory and determines whether to store the data block in the cache. The cache performs a first hash function on the data block in response to the processor determining to store the data block in the cache. The cache performs a second hash function on the data block if the first hash function results in a collision.