L. Arge, O. Procopiuc, S. Ramaswamy, T. Suel, and J. S. Vitter, Theory and practice of I/O-efficient algorithms for multidimensional batched searching problems, Proc. ACMSIAM Symp. on Discrete Algorithms, 1998, pp. 685--694.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....Subsequently, I O efficient algorithms have been developed for several problem domains, including computational geometry, graph theory, and string processing. Refer to recent surveys for references [3, 4, 32] The practical merits of the developed algorithms have been explored byanumber of authors [11, 31, 6, 5]. 1 For simplicitywe concentrate on the two first measures in this paper. It can be shown that the asymptotic internal memory computation time of our new R tree algorithms is the same as for the traditional algorithms. Much of this work uses the Transparent Parallel I O programming Environment ....

L. Arge, O. Procopiuc, S. Ramaswamy, T. Suel, and J. S. Vitter. Theory and practice of I/O-efficient algorithms for multidimensional batched searching problems. In Proc. ACM-SIAM Symp. on Discrete Algorithms, pages 685--694, 1998.

....subdivision so that a query can be answered in optimal O(log B N ) I Os. They also developed a structure for answering a batchofK point location queries in optimal O( N K) B) log M=B N ) I Os. Arge et al. 6] extended the batched result to general subdivisions (see also [15] and Arge et al. [5] to an off line dynamic setting in which a sequence of queries and updates are given in advance and all the queries should be answered as the sequence of operations are performed. Vahrenhold and Hinrichs [27] considered the problem under some practical assumptions about the input data. The only ....

....method can be used to make the static point location structure described in the previous section dynamic. The logarithmic method works for a (broad) class of so called decomposable searching problems first defined by Bentley [10] and previously considered in an external setting byArgeet al... [5]. Definition 2 (Arge et al. 5] Let P be a searching problem and let P(x# V ) denote the answer to P with respect to a set of objects V and a query x. P is called external decomposable,ifforany partition A [ B of V and for any query x, P(x# V ) can be computed in O(1) additional ....

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L. Arge, O. Procopiuc, S. Ramaswamy, T. Suel, and J. S. Vitter. Theory and practice of I/Oefficient algorithms for multidimensional batched searching problems. In Proc. ACM-SIAM Symp. on Discrete Algorithms, pages 685--694, 1998.

....and we EFFICIENT CROSS TREES FOR EXTERNAL MEMORY 5 refer the reader to [10] for a comprehensive survey on this topic and a list of references. Recently, some elegant data structures [5, 19, 30, 32, 35, 36] were devised to support fast range queries in external memory, and Arge et al. [4] have dealt with some decomposable problems in external memory. However, none of these data structures seems to be able to support efficiently split and concatenate along any coordinate. Ravi and Singh [33] following up on a previous lower bound of Hellerstein et al. 18] considered the ....

L. Arge, O. Procopiuc, S. Ramaswamy, T. Suel, and J.S. Vitter. Theory and Practice of I/OEfficient Algorithms for Multidimensional Batched Searching Problems. In Proc. 9th Annual ACM-SIAM Symp. on Discrete Algorithms (1998).

....one disk block. Previous Related Work We first briefly review the work on I O techniques. In addition to early work on sorting and scientific computing [2, 28, 44] recently various researchers have been investigating external memory algorithms for graphs [1, 12] and for computational geometry [1, 3, 5, 6, 7, 10, 18, 21, 29, 38, 43]. As mentioned before, most of the results are theoretical, and yet the experiments of Chiang [11] Vengroff and Vitter [42] and Arge et al. 5] on some of these techniques show that they result in significant improvements over traditional algorithms in practice. As for isosurface extraction, ....

.... researchers have been investigating external memory algorithms for graphs [1, 12] and for computational geometry [1, 3, 5, 6, 7, 10, 18, 21, 29, 38, 43] As mentioned before, most of the results are theoretical, and yet the experiments of Chiang [11] Vengroff and Vitter [42] and Arge et al. [5] on some of these techniques show that they result in significant improvements over traditional algorithms in practice. As for isosurface extraction, there is a very rich literature. Here we only briefly review the results that focus on speeding up the search phase. We refer to [24] for an ....

L. Arge, O. Procopiuc, S. Ramaswamy, T. Suel, and J. S. Vitter. Theory and practice of I/Oefficient algorithms for multidimensional batched searching problems. In Proc. ACM-SIAM Symp. on Discrete Algorithms, 1998.

....addition to early work on sorting and scientific computing, recently there have been I O algorithms for graphs and for computational geometry; see [10, 11] for the references. Although most of the results are theoretical, the experiments of Chiang [8] Vengroff and Vitter [27] and Arge et al. [2] on some of these techniques show that they result in significant improvements over traditional algorithms in practice. Teller et al. 24] describe a system to compute radiosity solutions for polygonal environments larger than main memory, and Funkhouser et al. 15] present prefetching techniques ....

L. Arge, O. Procopiuc, S. Ramaswamy, T. Suel, and J. S. Vitter. Theory and practice of I/O-efficient algorithms for multidimensional batched searching problems. In Proc. ACM-SIAM Symp. on Discrete Algorithms, 1998.

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L. Arge, O. Procopiuc, S. Ramaswamy, T. Suel, and J. S. Vitter, Theory and practice of I/O-efficient algorithms for multidimensional batched searching problems, Proc. ACMSIAM Symp. on Discrete Algorithms, 1998, pp. 685--694.

....algorithms that minimize the input output communication (I O) performed when solving a given problem. The area was effectively started in the late eighties by Aggarwal and Vitter [6] and subsequently I O algorithms have been developed for several problem domains, including computational geometry [29, 7, 13, 14, 4, 15, 31, 38, 39, 41, 3, 44, 2, 12, 13, 16, 28, 30, 44], graph algorithms [17, 7, 33, 1, 21, 8, 27, 35, 40] and string processing [25, 26, 11, 20] Also I O performance can often be improved if many disks can efficiently be used in parallel and the use of parallel disks has received a lot of theoretical attention. Recent surveys of theoretical ....

L. Arge, O. Procopiuc, S. Ramaswamy, T. Suel, and J. S. Vitter. Theory and practice of I/O-efficient algorithms for multidimensional batched searching problems. In Proc. ACMSIAM Symp. on Discrete Algorithms, pages 685--694, 1998.

....where inputs are coming in from multiple processors. 1. 1 Summary of this Paper We present a new algorithm for the filter step called Scalable Sweeping Based Spatial Join (SSSJ) The algorithm uses several techniques for I O efficient computing recently proposed in computational geometry [APR 98, GTVV93, Arg95, AVV98, Arg97] plus the well known internal memory plane sweeping technique (see, e.g. PS85] It achieves theoretically optimal worst case bounds on both internal computation time and I O transfers, while also being efficient on the more wellbehaved data sets common in ....

....describe a spatial join algorithm that is worst case optimal in terms of the number of I O transfers. This algorithm will be used as a building block in the SSSJ algorithm described in the next section. We point out that this section is based on the results and theoretical framework developed in [APR 98] The algorithm uses the distribution sweeping technique developed in [GTVV93] and further developed in [Arg95, AVV98] Following Aggarwal and Vitter [AV88] we use the following I O model: We make the assumption that each access to disk transmits one disk block with units of data, and we count ....

L. Arge, O. Procopiuc, S. Ramaswamy, T. Suel, and J. S. Vitter. Theory and practice of I/Oefficient algorithms for multidimensional batched searching problems. In Proc. ACM-SIAM Symp. on Discrete Algorithms, pages 685--694, 1998.

....et al. 4] that even for very large real life data sets, the maximum size of the data structures will be relatively small. To handle cases where the structures do not fit in memory, SSSJ combines the plane sweep approach with an I O optimal algorithm based on the distribution sweeping technique [5, 11]. In all experiments performed for this study the data structures were always significantly smaller than the available internal memory, and thus SSSJ essentially consists of a sorting step followed by a single scan over the data. Implementation. Our implementation of SSSJ is the same as that in ....

L. Arge, O. Procopiuc, S. Ramaswamy, T. Suel, and J. S. Vitter. Theory and practice of I/Oefficient algorithms for multidimensional batched searching problems. In ACM-SIAM Symp. on Discrete Algorithms, pages 685--694, 1998.

No context found.

L. Arge, O. Procopiuc, S. Ramaswamy, T. Suel, and J. S. Vitter. Theory and practice of I/Oefficient algorithms for multidimensional batched searching problems. In Proc. ACM-SIAM Symp. on Discrete Algorithms, pages 685--694, 1998.

....subdivision so that a query can be answered in optimal O(log B N) I Os. They also developed a structure for answering a batch of K point location queries in optimal O( N K) B) log M=B N) I Os. Arge et al. 6] extended the batched result to general subdivisions (see also [15] and Arge et al. [5] to an off line dynamic setting in which a sequence of queries and updates are given in advance and all the 1 A polygon is called monotone in direction if any line in direction =2 intersects the polygon in a connected interval; a convex polygon is monotone in every direction. A planar ....

....the method can be used to make the static point location structure described in the previous section dynamic. The logarithmic method works for a (broad) class of so called decomposable searching problems first defined by Bentley [10] and previously considered in an external setting by Arge et al. [5]. Definition 2 (Arge et al. 5] Let P be a searching problem and let P(x; V ) denote the answer to P with respect to a set of objects V and a query x. P is called external decomposable, if for any partition A [ B of V and for any query x, P(x; V ) can be computed in O(1) additional I Os given ....

[Article contains additional citation context not shown here]

L. Arge, O. Procopiuc, S. Ramaswamy, T. Suel, and J. S. Vitter. Theory and practice of I/Oefficient algorithms for multidimensional batched searching problems. In Proc. ACM-SIAM Symp. on Discrete Algorithms, pages 685--694, 1998.

....The interval tree variant that was implemented can be up to a logarithmic factor away from the optimum in the worst case. 4 In order to achieve acceptable performance even under worst case distributions, SSSJ combines the plane sweep approach with the worst case I O optimal algorithm proposed in [3] that is based on the distribution sweeping technique [3, 10] However, this worst case I O optimal algorithm, which involves a partitioning step along a single dimension, is only invoked in the case when the internal memory data structure runs out of memory. In all the experiments performed for ....

....to a logarithmic factor away from the optimum in the worst case. 4 In order to achieve acceptable performance even under worst case distributions, SSSJ combines the plane sweep approach with the worst case I O optimal algorithm proposed in [3] that is based on the distribution sweeping technique [3, 10]. However, this worst case I O optimal algorithm, which involves a partitioning step along a single dimension, is only invoked in the case when the internal memory data structure runs out of memory. In all the experiments performed for this study, this data structure was always significantly ....

L. A. Arge, O. Procopiuc, S. Ramaswamy, T. Suel, and J. S. Vitter. Theory and practice of I/O-efficient algorithms for multidimensional batched searching problems. In Proceedings of the Ninth Annual ACM-SIAM Symposium on Discrete Algorithms, pages 685--694. Association for Computing Machinery, 1998.

No context found.

L. Arge, O. Procopiuc, S. Ramaswamy, T. Suel, and J. S. Vitter, Theory and practice of I/O-efficient algorithms for multidimensional batched searching problems, Proc. ACM-SIAM Symp. on Discrete Algorithms, 1998, pp. 685--694.

No context found.

L. Arge, O. Procopiuc, S. Ramaswamy, T. Suel, and J. S. Vitter. Theory and practice of I/O-efficient algorithms for multidimensional batched searching problems. In Proc. ACM-SIAM Symp. on Discrete Algorithms (to appear), 1998.

....techniques of Section 3. In practice, disk striping may be sufficient. For online problems, disk striping will convert optimal bounds for the case D = 1 into optimal bounds for D 1. EXTERNAL MEMORY ALGORITHMS AND DATA STRUCTURES 19 Goodrich et al. 69] Zhu [148] Arge et al. 23] Arge et al. [21], and Crauser et al. 50, 51] develop EM algorithms for those problems using the following EM paradigms for batched problems: Distribution sweeping: a generalization of the distribution paradigm of Section 3 for externalizing plane sweep algorithms; Persistent B trees: an offline method for ....

....The remaining end portions of h (which partially span a strip) are passed recursively to the next level, along with the vertical segments. After the initial sorting preprocessing, each of the O(log m n) levels of recursion requires O(n) I Os, yielding the desired bound (5. 1) Arge et al. [21] develop a unified approach to distribution sweep in higher dimensions. A central operation in spatial databases is spatial join. A common preprocessing step is to find the pairwise intersections of the bounding boxes of the objects involved in the spatial join. The problem of intersecting ....

[Article contains additional citation context not shown here]

L. Arge, O. Procopiuc, S. Ramaswamy, T. Suel, and J. S. Vitter. Theory and practice of I/O-efficient algorithms for multidimensional batched searching problems. In Proceedings of the ACM-SIAM Symposium on Discrete Algorithms, 685--694, 1998.

....geometry problems. It is shown how data structures based on the buffer tree can be used in the standard internal memory plane sweep algorithm for a number of problems. In [53] two techniques called batched construction of persistent B trees and batched filtering are also discussed. In [18] some results from [53, 12] are extended and generalized, and some external memory computational geometry results are also reported in [49, 99] In [19] efficient I O algorithms for a large number of problems involving line segments in the plane are designed by combining the ideas of distribution ....

....line segments in the plane are designed by combining the ideas of distribution sweeping, batched filtering, buffer trees and a new technique, which can be regarded as an external memory version of fractional cascading [31] Most of these problems have important applications in GIS systems. In [32, 33, 18] some experimental results on the practical performance of external memory algorithms for computational geometry problems are reported. We divide our survey of external memory computational geometry into four main parts. In the next section we illustrate the distribution sweeping and the data ....

[Article contains additional citation context not shown here]

L. Arge, O. Procopiuc, S. Ramaswamy, T. Suel, and J. S. Vitter. Theory and practice of I/Oefficient algorithms for multidimensional batched searching problems. In Proc. ACM-SIAM Symp. on Discrete Algorithms (to appear), 1998.

....bound for sorting in internal memory. Work has also been done on matrix algebra and related problems arising in scientific computation [3, 51, 52] More recently, researchers have designed external memory algorithms for a number of problems in different areas, such as in computational geometry [32, 5, 53, 31, 2, 11, 34, 44, 47, 12, 50, 17, 1], string processing [28, 29, 9] and graph theoretic computation [6, 24, 38, 35] Some encouraging experimental results regarding the practical merits of the developed algorithms have also been obtained [23, 51, 11, 33] Recent surveys can be found in [7, 8] 1.3 Our Results In this paper, we ....

.... areas, such as in computational geometry [32, 5, 53, 31, 2, 11, 34, 44, 47, 12, 50, 17, 1] string processing [28, 29, 9] and graph theoretic computation [6, 24, 38, 35] Some encouraging experimental results regarding the practical merits of the developed algorithms have also been obtained [23, 51, 11, 33]. Recent surveys can be found in [7, 8] 1.3 Our Results In this paper, we combine and modify in novel ways several of the previously known techniques for designing efficient algorithms for external memory. In particular we use the distribution sweeping and batch filtering paradigms of [32] and ....

[Article contains additional citation context not shown here]

L. Arge, O. Procopiuc, S. Ramaswamy, T. Suel, and J. S. Vitter. Theory and practice of I/Oefficient algorithms for multidimensional batched searching problems. In Proc. ACM-SIAM Symp. on Discrete Algorithms, 1998.

....a monotone subdivision of size N so that a query can be answered in optimal O(log B N) I Os. They also developed a structure for answering a batch of K pointlocation queries in optimal O( N K B log M=B N) I Os. Arge et al. 5] extended the batched result to general subdivisions and Arge et al. [4] to an off line dynamic setting in which a sequence of queries and updates are given in advance and all the queries should be answered as the sequence of operations are performed. Vahrenhold and Hinrichs considered the problem under some practical assumptions about the input data [25] 1.2 Our ....

L. Arge, O. Procopiuc, S. Ramaswamy, T. Suel, and J. S. Vitter. Theory and practice of I/O-efficient algorithms for multidimensional batched searching problems. In Proc. ACM-SIAM Symp. on Discrete Algorithms, 685--694, 1998.

....I O efficient algorithms have been developed for several problem domains, including computational geometry, graph theory, and string processing. Refer to recent surveys for references [3, 4, 32] The practical merits of the developed algorithms have been explored by a number of authors [11, 31, 6, 5]. Much of this work uses the Transparent Parallel I O programming Environment (TPIE) 29, 30, 31] TPIE is a set of C functions and templated classes that allow for simple, efficient, and portable implementation of I O algorithms. 1.2 Previous results on bulk operations on R trees The R tree, ....

L. Arge, O. Procopiuc, S. Ramaswamy, T. Suel, and J. S. Vitter. Theory and practice of I/Oefficient algorithms for multidimensional batched searching problems. In Proc. ACM-SIAM Symp. on Discrete Algorithms, pages 685--694, 1998.

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