The Stanford GraphBase: a platform for combinatorial computing
The Stanford GraphBase: a platform for combinatorial computing
Computer organization & design: the hardware/software interface
Computer organization & design: the hardware/software interface
The art of computer programming, volume 3: (2nd ed.) sorting and searching
The art of computer programming, volume 3: (2nd ed.) sorting and searching
STL tutorial and reference guide, second edition: C++ programming with the standard template library
STL tutorial and reference guide, second edition: C++ programming with the standard template library
Cache performance for selected SPEC CPU2000 benchmarks
ACM SIGARCH Computer Architecture News
Individual displacements for linear probing hashing with different insertion policies
ACM Transactions on Algorithms (TALG)
Exact distribution of individual displacements in linear probing hashing
ACM Transactions on Algorithms (TALG)
SFCS '85 Proceedings of the 26th Annual Symposium on Foundations of Computer Science
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Modern-day computers are characterized by a striking contrast between the processing power of the CPU and the latency of main memory accesses. If the data processed is both large compared to processor caches and sparse or high-dimensional in nature, as is commonly the case in complex network research, the main memory latency can become a performace bottleneck. In this article, we present a cache-efficient data structure, a variant of a linear probing hash table, for representing edge sets of such networks. The performance benchmarks show that it is, indeed, quite superior to its commonly used counterparts in this application. In addition, its memory footprint only exceeds the absolute minimum by a small constant factor. The practical usability of our approach has been well demonstrated in the study of very large real-world networks.