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The buffer tree: A new technique for optimal I/Oalgorithms
 University of Aarhus
, 1995
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A New Data Structure for Representing Sorted Lists
, 1982
"... In this paper we explore the use of weak Btrees to represent sorted lists. In weak Btrees each node has at least a and at most b sons where 2a<b. We analyse the worst case cost of sequences of insertions and deletions in weak Btrees. This leads to a new data structure (levellinked weak Btr ..."
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Cited by 93 (0 self)
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In this paper we explore the use of weak Btrees to represent sorted lists. In weak Btrees each node has at least a and at most b sons where 2a<b. We analyse the worst case cost of sequences of insertions and deletions in weak Btrees. This leads to a new data structure (levellinked weak Btrees) for representing sorted lists when the access pattern exhibits a (timevarying) locality of reference. Our structure is substantially simpler than the one proposed in [7], yet it has many of its properties. Our structure is as simple as the one proposed in [5], but our structure can treat arbitrary sequences of insertions and deletions whilst theirs can only treat noninteracting insertions and deletions. We also show that weak Btrees support concurrent operations in an efficient way.
Optimal Dynamic Interval Management in External Memory (Extended Abstract)
 IN PROC. IEEE SYMP. ON FOUNDATIONS OF COMP. SCI
, 1996
"... We present a space and I/Ooptimal externalmemory data structure for answering stabbing queries on a set of dynamically maintained intervals. Our data structure settles an open problem in databases and I/O algorithms by providing the first optimal externalmemory solution to the dynamic interval m ..."
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Cited by 81 (20 self)
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We present a space and I/Ooptimal externalmemory data structure for answering stabbing queries on a set of dynamically maintained intervals. Our data structure settles an open problem in databases and I/O algorithms by providing the first optimal externalmemory solution to the dynamic interval management problem, which is a special case of 2dimensional range searching and a central problem for objectoriented and temporal databases and for constraint logic programming. Our data structure simultaneously uses optimal linear space (that is, O(N/B) blocks of disk space) and achieves the optimal O(log B N + T/B) I/O query bound and O(log B N ) I/O update bound, where B is the I/O block size and T the number of elements in the answer to a query. Our structure is also the first optimal external data structure for a 2dimensional range searching problem that has worstcase as opposed to amortized update bounds. Part of the data structure uses a novel balancing technique for efficient worstcase manipulation of balanced trees, which is of independent interest.
Efficient ExternalMemory Data Structures and Applications
, 1996
"... In this thesis we study the Input/Output (I/O) complexity of largescale problems arising e.g. in the areas of database systems, geographic information systems, VLSI design systems and computer graphics, and design I/Oefficient algorithms for them. A general theme in our work is to design I/Oeffic ..."
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Cited by 38 (9 self)
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In this thesis we study the Input/Output (I/O) complexity of largescale problems arising e.g. in the areas of database systems, geographic information systems, VLSI design systems and computer graphics, and design I/Oefficient algorithms for them. A general theme in our work is to design I/Oefficient algorithms through the design of I/Oefficient data structures. One of our philosophies is to try to isolate all the I/O specific parts of an algorithm in the data structures, that is, to try to design I/O algorithms from internal memory algorithms by exchanging the data structures used in internal memory with their external memory counterparts. The results in the thesis include a technique for transforming an internal memory tree data structure into an external data structure which can be used in a batched dynamic setting, that is, a setting where we for example do not require that the result of a search operation is returned immediately. Using this technique we develop batched dynamic external versions of the (onedimensional) rangetree and the segmenttree and we develop an external priority queue. Following our general philosophy we show how these structures can be used in standard internal memory sorting algorithms
LEDASM: Extending LEDA to secondary memory
 In Proc. Workshop on Algorithm Engineering
, 1999
"... Abstract. During the last years, many software libraries for incore computation have been developed. Most internal memory algorithms perform very badly when used in an external memory setting. We introduce LEDASM that extends the LEDAlibrary [22] towards secondary memory computation. LEDASM use ..."
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Cited by 10 (2 self)
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Abstract. During the last years, many software libraries for incore computation have been developed. Most internal memory algorithms perform very badly when used in an external memory setting. We introduce LEDASM that extends the LEDAlibrary [22] towards secondary memory computation. LEDASM uses I/Oecient algorithms and data structures that do not suer from the so called I/O bottleneck. LEDA is used for incore computation. We explain the design of LEDASM and report on performance results. 1
On the performance of LEDASM
, 1998
"... We report on the performance of a library prototype for external memory algorithms and data structures called LEDASM, where SM is an acronym for secondary memory. Our library is based on LEDA and intended to complement it for large data. We present performance results of our external memory lib ..."
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Cited by 1 (0 self)
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We report on the performance of a library prototype for external memory algorithms and data structures called LEDASM, where SM is an acronym for secondary memory. Our library is based on LEDA and intended to complement it for large data. We present performance results of our external memory library prototype and compare these results with corresponding results of LEDAs incore algorithms in virtual memory. The results show that even if only a small main memory is used for the external memory algorithms, they always outperform their incore counterpart. Furthermore we compare different implementations of external memory data structures and algorithms.