Buffer Root Internal Node Leaf Node

Computer processing speeds are increasing rapidly due to the evolution of faster chips, parallel processing of data, and more eecient software. Users today have access to an unprecedented amount of high quality, high resolution data through various technologies. This is resulting in a growing demand for higher performance input and output mechanisms in order to pass huge data sets from the external memory (EM), or disk system, through the relatively small main memory of the computer and back again. In recent years, research into external memory algorithms has been growing to keep pace with the demand for innovation in this area. EM algorithms for individual problems have been developed but few general purpose EM tools have been designed. A fundamental tool is the buuer tree, an external version of the (a,b)-tree. It can be used to satisfy a number of EM requirements such as sorting, priority queues, range searching, etc. in a straightforward and I/O-optimal manner. In this paper we describe an implementation of a buuer tree. We describe benchmarking tests which lead to an experimental determination of certain parameter values diierent from those originally suggested in the design of the data structure. We describe implementations of two algorithms based on the buuer tree: an external memory treesort, and an external memory priority queue. Our initial experiments with buuer tree sort for large problem sizes indicate that this algorithm easily outperforms similar algorithms based on internal memory techniques. With some tuning of the buuer tree parameters we are able to obtain performance consistent with theoretical predictions for the range of problem sizes tested. We include comparisons with TPIE Merge Sort. We conclude that (a) the buuer tree as a generic data structure appears to perform well in theory and practice, and (b) measuring I/O eeciency experimentally is an important topic that merits further attention.