CostCounter: A Better Method for Collision Mitigation in Cuckoo Hashing

IF 2.1 3区 计算机科学 Q3 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE ACM Transactions on Storage Pub Date : 2023-06-19 DOI:https://dl.acm.org/doi/10.1145/3596910
Haonan Wu, Shuxian Wang, Zhanfeng Jin, Yuhang Zhang, Ruyun Ma, Sijin Fan, Ruili Chao
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Abstract

Hardware is often required to support fast search and high-throughput applications. Consequently, the performance of search algorithms is limited by storage bandwidth. Hence, the search algorithm must be optimized accordingly. We propose a CostCounter (CC) algorithm based on cuckoo hashing and an Improved CostCounter (ICC) algorithm. A better path can be selected when collisions occur using a cost counter to record the kick-out situation. Our simulation results indicate that the CC and ICC algorithms can achieve more significant performance improvements than Random Walk (RW), Breadth First Search (BFS), and MinCounter (MC). With two buckets and two slots per bucket, under the 95% memory load rate of the maximum load rate, CC and ICC are optimized on read-write times over 20% and 80% compared to MC and BFS, respectively. Furthermore, the CC and ICC algorithms achieve a slight improvement in storage efficiency compared with MC. In addition, we implement RW, MC, and the proposed algorithms using fine-grained locking to support a high throughput rate. From the test on field programmable gate arrays, we verify the simulation results and our algorithms optimize the maximum throughput over 23% compared to RW and 9% compared to MC under 95% of the memory capacity. The test results indicate that our CC and ICC algorithms can achieve better performance in terms of hardware bandwidth and memory load efficiency without incurring a significant resource cost.

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成本计数器:杜鹃哈希中一种更好的冲突缓解方法
通常需要硬件来支持快速搜索和高吞吐量应用程序。因此,搜索算法的性能受到存储带宽的限制。因此,搜索算法必须进行相应的优化。提出了一种基于布谷鸟哈希的CostCounter (CC)算法和一种改进的CostCounter (ICC)算法。当发生碰撞时,可以选择更好的路径,使用成本计数器记录踢球情况。仿真结果表明,CC和ICC算法比Random Walk (RW)、广度优先搜索(BFS)和MinCounter (MC)算法能取得更显著的性能改进。对于两个桶和每个桶两个槽,在最大负载率为95%的内存负载率下,CC和ICC的读写时间分别比MC和BFS高20%和80%。此外,与MC相比,CC和ICC算法在存储效率方面略有提高。此外,我们使用细粒度锁定实现RW, MC和所提出的算法以支持高吞吐率。通过对现场可编程门阵列的测试,我们验证了仿真结果,我们的算法在95%的内存容量下,与RW相比优化了23%的最大吞吐量,与MC相比优化了9%的最大吞吐量。测试结果表明,我们的CC和ICC算法在硬件带宽和内存负载效率方面可以获得更好的性能,而不会产生显着的资源成本。
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来源期刊
ACM Transactions on Storage
ACM Transactions on Storage COMPUTER SCIENCE, HARDWARE & ARCHITECTURE-COMPUTER SCIENCE, SOFTWARE ENGINEERING
CiteScore
4.20
自引率
5.90%
发文量
33
审稿时长
>12 weeks
期刊介绍: The ACM Transactions on Storage (TOS) is a new journal with an intent to publish original archival papers in the area of storage and closely related disciplines. Articles that appear in TOS will tend either to present new techniques and concepts or to report novel experiences and experiments with practical systems. Storage is a broad and multidisciplinary area that comprises of network protocols, resource management, data backup, replication, recovery, devices, security, and theory of data coding, densities, and low-power. Potential synergies among these fields are expected to open up new research directions.
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