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In recent years the Cache-Oblivious model of external memory computation hasprovided an attractive theoretical basis for the analysis of algorithms onmassive datasets. Much progress has been made in discovering algorithms thatare asymptotically optimal or near optimal. However, to date there are stillrelatively few successful experimental studies. In this paper we compare twodifferent Cache-Oblivious priority queues based on the Funnel and Bucket Heapand apply them to the single source shortest path problem on graphs withpositive edge weights. Our results show that when RAM is limited and data isswapping to external storage, the Cache-Oblivious priority queues achieveorders of magnitude speedups over standard internal memory techniques. However,for the single source shortest path problem both on simulated and real worldgraph data, these speedups are markedly lower due to the time required toaccess the graph adjacency list itself.

An Empirical Study of Cache-Oblivious Priority Queues and their Application to the Shortest Path Problem