CostCounter: A Better Method for Collision Mitigation in Cuckoo Hashing

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 FPGA, 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.