Results 1 - 10
of
132
Analysis of the clustering properties of the Hilbert space-filling 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 spatio-temporal databases and image compression. In these applications, one of the most desired properties from such linear mappings is clustering, whic ..."
Abstract
-
Cited by 192 (12 self)
- Add to MetaCart
(Show Context)
AbstractÐSeveral schemes for the linear mapping of a multidimensional space have been proposed for various applications, such as access methods for spatio-temporal 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 space-filling curve achieves the best clustering [1], [14]. In this paper, we analyze the clustering property of the Hilbert space-filling curve by deriving closed-form 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.
Designing Pixel-Oriented Visualization Techniques: Theory and Applications,”
- IEEE Trans. Visualization and Computer Graphics,
, 2000
"... ..."
(Show Context)
Visualization Techniques for Mining Large Databases: A Comparison
- IEEE Transactions on Knowledge and Data Engineering
, 1996
"... Visual data mining techniques have proven to be of high value in exploratory data analysis and they also have a high potential for mining large databases. In this article, we describe and evaluate a new visualization-based approach to mining large databases. The basic idea of our visual data mining ..."
Abstract
-
Cited by 116 (1 self)
- Add to MetaCart
(Show Context)
Visual data mining techniques have proven to be of high value in exploratory data analysis and they also have a high potential for mining large databases. In this article, we describe and evaluate a new visualization-based approach to mining large databases. The basic idea of our visual data mining techniques is to represent as many data items as possible on the screen at the same time by mapping each data value to a pixel of the screen and arranging the pixels adequately. The major goal of this article is to evaluate our visual data mining techniques and to compare them to other well-known visualization techniques for multidimensional data: the parallel coordinate and stick figure visualization techniques. For the evaluation of visual data mining techniques, in the first place the perception of properties of the data counts, and only in the second place the CPU time and the number of secondary storage accesses are important. In addition to testing the visualization techniques using re...
On the construction of some capacity-approaching 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 ..."
Abstract
-
Cited by 84 (2 self)
- Add to MetaCart
(Show Context)
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-channel coding schemes. We first show some examples of sources and channels where no coding is optimal for all values of the signal-to-noise ratio (SNR). When the source bandwidth is greater than the channel bandwidth, joint coding schemes based on space-filling curves and other families of curves are proposed. For uniform sources and modulo channels, our coding scheme based on space-filling curves operates within 1.1 dB of Shannon’s rate-distortion bound. For Gaussian sources and additive white Gaussian noise (AWGN) channels, we can achieve within 0.9 dB of the rate-distortion bound. The second scheme is based on low-density parity-check (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
On Partitioning Dynamic Adaptive Grid Hierarchies
- Proceedings of the 29th Annual Hawaii International Conference on System Sciences
, 1996
"... This paper presents a computationally efficient runtime partitioning and load-balancing scheme for the Distributed Adaptive Grid Hierarchies that underlie adaptive mesh-refinement methods. The partitioning scheme yields an efficient parallel computational structure that maintains locality to reduce ..."
Abstract
-
Cited by 78 (23 self)
- Add to MetaCart
(Show Context)
This paper presents a computationally efficient runtime partitioning and load-balancing scheme for the Distributed Adaptive Grid Hierarchies that underlie adaptive mesh-refinement methods. The partitioning scheme yields an efficient parallel computational structure that maintains locality to reduce communications. Further, it enables dynamic re-partitioning and loadbalancing of the adaptive grid hierarchy to be performed cost-effectively. The run-time partitioning support presented has been implemented within the framework of a data-management infrastructure supporting dynamic distributed data-structures for parallel adaptive numerical techniques. This infrastructure is the foundational layer of a computational toolkit for the Binary Black-Hole NSF Grand Challenge project. 1 Introduction Dynamically adaptive methods for the solution of partial differential equations that employ locally optimal approximations can yield highly advantageous ratios for cost/accuracy when compared to metho...
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, non-programmable array attribute. ..."
Abstract
-
Cited by 76 (5 self)
- Add to MetaCart
(Show Context)
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, non-programmable 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 re-ordering 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 (2--5% of total running time) and high performance benefits (reducing execution time by factors of 1.1-2.5); that they have smooth performance curves, both across a wide range of problem sizes and over representative cache architectures; and that recursion-based control structures may be needed to fully exploit their potential.
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 column-major or row-major array layouts i ..."
Abstract
-
Cited by 54 (5 self)
- Add to MetaCart
(Show Context)
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 column-major or row-major 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 1.2--2.5) for the standard algorithm, they offer little improvement for Strassen's and Winograd's algorithms;...
Pixel-oriented Visualization Techniques for Exploring Very Large Databases
- Journal of Computational and Graphical Statistics
, 1996
"... An important goal of visualization technology is to support the exploration and analysis of very large amounts of data. In this paper, we describe a set of pixeloriented visualization techniques which use each pixel of the display to visualize one data value and therefore allow the visualization of ..."
Abstract
-
Cited by 40 (3 self)
- Add to MetaCart
An important goal of visualization technology is to support the exploration and analysis of very large amounts of data. In this paper, we describe a set of pixeloriented visualization techniques which use each pixel of the display to visualize one data value and therefore allow the visualization of the largest amount of data possible. Most of the techniques have been specifically designed for visualizing and querying large databases. The techniques may be divided into query-independent techniques which directly visualize the data (or a certain portion of it) and query-dependent techniques which visualize the data in the context of a specific query. Examples for the class of query-independent techniques are the screen-filling curve and recursive pattern techniques. The screen-filling curve techniques are based on the well-known Morton and Peano-Hilbert curve algorithms, and the recursive pattern technique is based on a generic recursive scheme which generalizes a wide range of pixel-ori...
Recursive Array Layouts and Fast Matrix Multiplication
, 1999
"... The performance of both serial and parallel implementations of matrix multiplication is highly sensitive to memory system behavior. False sharing and cache conflicts cause traditional column-major or row-major array layouts to incur high variability in memory system performance as matrix size var ..."
Abstract
-
Cited by 39 (0 self)
- Add to MetaCart
(Show Context)
The performance of both serial and parallel implementations of matrix multiplication is highly sensitive to memory system behavior. False sharing and cache conflicts cause traditional column-major or row-major array layouts to incur high variability in memory system performance as matrix size varies. This paper investigates the use of recursive array layouts to improve performance and reduce variability. Previous work on recursive matrix multiplication is extended to examine several recursive array layouts and three recursive algorithms: standard matrix multiplication, and the more complex algorithms of Strassen and Winograd. While recursive layouts significantly outperform traditional layouts (reducing execution times by a factor of 1.2--2.5) for the standard algorithm, they offer little improvement for Strassen's and Winograd's algorithms. For a purely sequential implementation, it is possible to reorder computation to conserve memory space and improve performance between ...
Distributed Dynamic Data-Structures for Parallel Adaptive Mesh-Refinement
- PROCEEDINGS OF THE INTERNATIONAL CONFERENCE FOR HIGH PERFORMANCE COMPUTING
, 1995
"... This paper presents the design and implementation of dynamic distributed data-structures to support parallel adaptive (multigrid) finite difference codes based on hierarchical adaptive mesh-refinement (AMR) techniques for the solution of partial differential equations. The abstraction provided by th ..."
Abstract
-
Cited by 38 (11 self)
- Add to MetaCart
(Show Context)
This paper presents the design and implementation of dynamic distributed data-structures to support parallel adaptive (multigrid) finite difference codes based on hierarchical adaptive mesh-refinement (AMR) techniques for the solution of partial differential equations. The abstraction provided by the datastructures is a dynamic hierarchical grid where operations on the grid are independent of its distribution across processors in a parallel execution environment, and of the number of levels in the grid hierarchy. The distributed dynamic data-structures have been implemented aspart of a computational toolkit for the Binary Black-Hole NSF Grand Challenge project.