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Geometric Range Searching and Its Relatives
 CONTEMPORARY MATHEMATICS
"... ... process a set S of points in so that the points of S lying inside a query R region can be reported or counted quickly. Wesurvey the known techniques and data structures for range searching and describe their application to other related searching problems. ..."
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Cited by 254 (41 self)
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... process a set S of points in so that the points of S lying inside a query R region can be reported or counted quickly. Wesurvey the known techniques and data structures for range searching and describe their application to other related searching problems.
On Packing Rtrees
 In ACM CIKM
, 1993
"... – main idea; file structure – algorithms: insertion/split – deletion – search: range, nn, spatial joins – performance analysis – variations (packed; hilbert;...) 15721 Copyright: C. Faloutsos (2001) 2 Problem • Given a collection of geometric objects (points, lines, polygons,...) • organize them on ..."
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Cited by 221 (15 self)
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– main idea; file structure – algorithms: insertion/split – deletion – search: range, nn, spatial joins – performance analysis – variations (packed; hilbert;...) 15721 Copyright: C. Faloutsos (2001) 2 Problem • Given a collection of geometric objects (points, lines, polygons,...) • organize them on disk, to answer spatial queries (range, nn, etc) 15721 Copyright: C. Faloutsos (2001) 3 1 (Who cares?)
Hilbert Rtree: An improved Rtree using fractals
, 1994
"... We propose a new Rtree structure that outperforms all the older ones. The heart of the idea is to facilitate the deferred splitting approach in Rtrees. This is done by proposing an ordering on the Rtree nodes. This ordering has to be 'good', in the sense that it should group 'simil ..."
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Cited by 187 (10 self)
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We propose a new Rtree structure that outperforms all the older ones. The heart of the idea is to facilitate the deferred splitting approach in Rtrees. This is done by proposing an ordering on the Rtree nodes. This ordering has to be 'good', in the sense that it should group 'similar' data rectangles together, to minimize the area and perimeter of the resulting minimum bounding rectangles (MBRs). Following [19] we have chosen the socalled '2Dc' method, which sorts rectangles according to the Hilbert value of the center of the rectangles. Given the ordering, every node has a welldefined set of sibling nodes; thus, we can use deferred splitting. By adjusting the split policy, the Hilbert Rtree can achieve as high utilization as desired. To the contrary, the R tree has no control over the space utilization, typically achieving up to 70%. We designed the manipulation algorithms in detail, and we did a full implementation of the Hilbert Rtree. Our experiments show that the '2to...
Analysis of the clustering properties of the Hilbert spacefilling curve
 IEEE Transactions on Knowledge and Data Engineering
, 2001
"... AbstractÐSeveral schemes for the linear mapping of a multidimensional space have been proposed for various applications, such as access methods for spatiotemporal databases and image compression. In these applications, one of the most desired properties from such linear mappings is clustering, whic ..."
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Cited by 145 (11 self)
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AbstractÐSeveral schemes for the linear mapping of a multidimensional space have been proposed for various applications, such as access methods for spatiotemporal databases and image compression. In these applications, one of the most desired properties from such linear mappings is clustering, which means the locality between objects in the multidimensional space being preserved in the linear space. It is widely believed that the Hilbert spacefilling curve achieves the best clustering [1], [14]. In this paper, we analyze the clustering property of the Hilbert spacefilling curve by deriving closedform formulas for the number of clusters in a given query region of an arbitrary shape (e.g., polygons and polyhedra). Both the asymptotic solution for the general case and the exact solution for a special case generalize previous work [14]. They agree with the empirical results that the number of clusters depends on the hypersurface area of the query region and not on its hypervolume. We also show that the Hilbert curve achieves better clustering than the z curve. From a practical point of view, the formulas given in this paper provide a simple measure that can be used to predict the required disk access behaviors and, hence, the total access time.
Fractals for Secondary Key Retrieval
"... In this paper we propose the use of fractals and especially the Hilbert curve, in order to design good distancepreserving mappings. Such mappings improve the performance of secondarykey and spatial access methods, where multidimensional points have to be stored on an 1dimensional medium (e.g., ..."
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Cited by 143 (18 self)
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In this paper we propose the use of fractals and especially the Hilbert curve, in order to design good distancepreserving mappings. Such mappings improve the performance of secondarykey and spatial access methods, where multidimensional points have to be stored on an 1dimensional medium (e.g., disk). Good clustering reduces the number of disk accesses on retrieval, improving the response time. Our experiments on range queries and nearest neighbor queries showed that the proposed Hilbert curve achieves better clustering than older methods (&quot;bitshuffling&quot;, or Peano curve), for every situation we tried.
Declustering Using Fractals
 In Proceedings of the 2nd International Conference on Parallel and Distributed Information Systems
, 1993
"... We propose a method to achieve declustering for cartesian product files on M units. The focus is on range queries, as opposed to partial match queries that older declustering methods have examined. Our method uses a distancepreserving mapping, namely, the Hilbert curve, to impose a linear ordering ..."
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Cited by 82 (1 self)
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We propose a method to achieve declustering for cartesian product files on M units. The focus is on range queries, as opposed to partial match queries that older declustering methods have examined. Our method uses a distancepreserving mapping, namely, the Hilbert curve, to impose a linear ordering on the multidimensional points (buckets); then, it traverses the buckets according to this ordering, assigning buckets to disks in a roundrobin fashion. Thanks to the good distancepreserving properties of the Hilbert curve, the end result is that each disk contains buckets that are far away in the linear ordering, and, most probably, far away in the kd address space. This is exactly the goal of declustering. Experiments show that these intuitive arguments lead indeed to good performance: the proposed method performs at least as well or better than older declustering schemes. Categories and Subject Descriptors: E.1 [Data Structures]; E.5 [Files]; H.2.2 [Data Base Management]: Physical Des...
Nonlinear Array Layouts for Hierarchical Memory Systems
, 1999
"... Programming languages that provide multidimensional arrays and a flat linear model of memory must implement a mapping between these two domains to order array elements in memory. This layout function is fixed at language definition time and constitutes an invisible, nonprogrammable array attribute. ..."
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Cited by 73 (5 self)
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Programming languages that provide multidimensional arrays and a flat linear model of memory must implement a mapping between these two domains to order array elements in memory. This layout function is fixed at language definition time and constitutes an invisible, nonprogrammable array attribute. In reality, modern memory systems are architecturally hierarchical rather than flat, with substantial differences in performance among different levels of the hierarchy. This mismatch between the model and the true architecture of memory systems can result in low locality of reference and poor performance. Some of this loss in performance can be recovered by reordering computations using transformations such as loop tiling. We explore nonlinear array layout functions as an additional means of improving locality of reference. For a benchmark suite composed of dense matrix kernels, we show by timing and simulation that two specific layouts (4D and Morton) have low implementation costs (25% of total running time) and high performance benefits (reducing execution time by factors of 1.12.5); that they have smooth performance curves, both across a wide range of problem sizes and over representative cache architectures; and that recursionbased control structures may be needed to fully exploit their potential.
Size Separation Spatial Join
, 1997
"... We introduce a new algorithm to compute the spatial join of two or more spatial data sets, when indexes are not available on them. Size Separation Spatial Join (S 3 J) imposes a hierarchical decomposition of the data space and, in contrast with previous approaches, requires no replication of entit ..."
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Cited by 60 (2 self)
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We introduce a new algorithm to compute the spatial join of two or more spatial data sets, when indexes are not available on them. Size Separation Spatial Join (S 3 J) imposes a hierarchical decomposition of the data space and, in contrast with previous approaches, requires no replication of entities from the input data sets. Thus its execution time depends only on the sizes of the joined data sets. We describe S 3 J and present an analytical evaluation of its I/O and processor requirements comparing them with those of previously proposed algorithms for the same problem. We show that S 3 J has relatively simple cost estimation formulas that can be exploited by a query optimizer. S 3 J can be efficiently implemented using software already present in many relational systems. In addition, we introduce Dynamic Spatial Bitmaps (DSB), a new technique that enables S 3 J to dynamically or statically exploit bitmap query processing techniques. Finally, we present experimental result...
On the construction of some capacityapproaching coding schemes
, 2000
"... This thesis proposes two constructive methods of approaching the Shannon limit very closely. Interestingly, these two methods operate in opposite regions, one has a block length of one and the other has a block length approaching infinity. The first approach is based on novel memoryless joint source ..."
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Cited by 58 (2 self)
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This thesis proposes two constructive methods of approaching the Shannon limit very closely. Interestingly, these two methods operate in opposite regions, one has a block length of one and the other has a block length approaching infinity. The first approach is based on novel memoryless joint sourcechannel coding schemes. We first show some examples of sources and channels where no coding is optimal for all values of the signaltonoise ratio (SNR). When the source bandwidth is greater than the channel bandwidth, joint coding schemes based on spacefilling curves and other families of curves are proposed. For uniform sources and modulo channels, our coding scheme based on spacefilling curves operates within 1.1 dB of Shannon’s ratedistortion bound. For Gaussian sources and additive white Gaussian noise (AWGN) channels, we can achieve within 0.9 dB of the ratedistortion bound. The second scheme is based on lowdensity paritycheck (LDPC) codes. We first demonstrate that we can translate threshold values of an LDPC code between channels accurately using a simple mapping. We develop some models for density evolution
Recursive Array Layouts and Fast Parallel Matrix Multiplication
 In Proceedings of Eleventh Annual ACM Symposium on Parallel Algorithms and Architectures
, 1999
"... Matrix multiplication is an important kernel in linear algebra algorithms, and the performance of both serial and parallel implementations is highly dependent on the memory system behavior. Unfortunately, due to false sharing and cache conflicts, traditional columnmajor or rowmajor array layouts i ..."
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Cited by 48 (4 self)
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Matrix multiplication is an important kernel in linear algebra algorithms, and the performance of both serial and parallel implementations is highly dependent on the memory system behavior. Unfortunately, due to false sharing and cache conflicts, traditional columnmajor or rowmajor array layouts incur high variability in memory system performance as matrix size varies. This paper investigates the use of recursive array layouts for improving the performance of parallel recursive matrix multiplication algorithms. We extend previous work by Frens and Wise on recursive matrix multiplication to examine several recursive array layouts and three recursive algorithms: standard matrix multiplication, and the more complex algorithms of Strassen and Winograd. We show that while recursive array layouts significantly outperform traditional layouts (reducing execution times by a factor of 1.22.5) for the standard algorithm, they offer little improvement for Strassen's and Winograd's algorithms;...