Hash Table Lookup Bounding Latency via Parallel Multi-Hash Access
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Solution Overview
Problem
Traditional hardware-based hash-table lookup solutions suffer from non-fixed and unbounded latency due to collisions, which can lead to unpredictable read times and excessive latency in key-value lookups.
Innovation Solution
The implementation of multi-hash operations, which involve using multiple hash functions in parallel to map entries into multiple hash tables, allowing for collision resolution by accessing relevant tables in parallel, thereby reducing latency to nearly one memory access time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If traditional hardware-based hash-table lookup solutions are used, then the structure is simple, but latency is unbounded and unpredictable
Solution Approach 1:
The patent divides the hash table into multiple separate tables (first hash table, second hash table, third hash table) and uses multiple hash functions to distribute entries across these tables. This segmentation allows parallel lookup operations across different tables, bounding the maximum latency to a predictable number of memory accesses while maintaining structural simplicity through modular table design.
Solution Approach 2:
The patent introduces a multi-dimensional lookup approach by applying multiple hash functions (first, second, and third hash functions) that map keys to different tables simultaneously. This dimensional expansion from a single hash function to multiple functions enables parallel search paths, transforming unbounded latency into bounded latency by limiting the number of tables to search.
2Loss of time
If multiple hash tables are used to reduce latency, then lookup time is bounded, but device complexity increases
Solution Approach 1:
The patent pre-computes and stores collision hints that indicate which tables contain entries for specific hash values before the lookup operation. This preliminary preparation allows the system to efficiently navigate the multi-table structure during lookup, reducing the need for complex runtime decision-making and minimizing the operational complexity of the multi-hash table architecture.
Solution Approach 2:
The patent introduces collision hints as intermediary data structures that mediate between the lookup key and the multiple hash tables. These hints act as guides that tell the system which tables to search, simplifying the lookup process by eliminating the need to exhaustively search all tables and reducing the operational complexity of managing multiple tables.
3Measurement precision
If collision resolution requires multiple memory accesses, then accuracy is maintained, but latency increases
Solution Approach 1:
The patent enables continuous parallel memory accesses across multiple hash tables simultaneously during the lookup operation. By initiating lookup operations in all relevant tables at the same time rather than sequentially, the system maintains accurate key-value matching while eliminating the cumulative latency of sequential accesses, achieving both precision and performance.
Solution Approach 2:
The patent resolves the latency-accuracy tradeoff by transitioning from sequential one-dimensional memory accesses to parallel multi-dimensional accesses. By simultaneously querying multiple tables through different hash functions, the system maintains comprehensive search coverage for accuracy while reducing total access time through parallelism.
Data Source
AI summary
Examples described herein relate to key-value lookups. A first index is calculated based on a first hash function and a received key. A first hash table including entries associated with a first hash calculation on a key is accessed. A collision hint table is accessed to identify any other hash table to search. If the collision hint table indicates any other table to search, the first hash table and the any other hash table are searched to identify an entry associated with an index that matches the first index.