Compact Parallel Hash Tables on the GPU

TL;DR

This paper introduces compact hash table schemes optimized for GPU architectures, demonstrating significant performance improvements in lookup and insertion throughput through theoretical analysis and CUDA implementation.

Contribution

It adapts compact hashing techniques to the GPU setting, providing new schemes and benchmarking them against existing methods.

Findings

Compact cuckoo hashing improves throughput by 10-20%.

Iceberg hashing achieves comparable performance to cuckoo hashing.

Both schemes support dynamic operations efficiently.

Abstract

On the GPU, hash table operation speed is determined in large part by cache line efficiency, and state-of-the-art hashing schemes thus divide tables into cache line-sized buckets. This raises the question whether performance can be further improved by increasing the number of entries that fit in such buckets. Known compact hashing techniques have not yet been adapted to the massively parallel setting, nor have they been evaluated on the GPU. We consider a compact version of bucketed cuckoo hashing, and a version of compact iceberg hashing suitable for the GPU. We discuss the tables from a theoretical perspective, and provide an open source implementation of both schemes in CUDA for comparative benchmarking. In terms of performance, the state-of-the-art cuckoo hashing benefits from compactness on lookups and insertions (most experiments show at least 10-20% increase in throughput), and the iceberg table benefits significantly, to the point of being comparable to compact cuckoo hashing--while supporting performant dynamic operation.