By using this strategy we develop a general visualization algorithm that can be used to compare the structural. Recognizing the prospect of substantial duplication of effort, the developers of these software projects came together to work under a unified software product. Analyzing the structure of java software systems by weighted. This is the only book to explain software optimization for embedded multi core systems helpful tips, tricks and design secrets from an intel programming expert, with detailed examples using the popular x86 architecture covers hot topics, including ultramobile devices, lowpower designs, pthreads vs. Visualization of cracks by using the local voronoi decompositions and distributed software. Roadmap for manycore visualization software in doe jeremy meredith oak ridge national laboratory. Ccvisu is a lightweight tool that takes as input a software graph model and computes a visual representation of the systems structure, i. The core of a graph is a maximal connected subgraph of degree. We feature implementations of the vertexcentric distributed protocol introduced by montresor.
It is extensively used in aiding the visualization of the network structure 3, 30, understanding and interpreting cooperative. Large scale networks fingerprinting and visualization using. Lanetvi is based on the k core decomposition of a network. Freeware network visualization software free download. Topdown software decomposition an approach for component. The core of this package is a multilayergraph, a class that inherits all properties from networkx.
We apply them to analyze maps obtained from the prominent internet mapping projects, using the lanetvi opensource software for its visualization topics. Software frameworks for visualization and analysis on nextgeneration multicore and manycore architectures, seventh workshop on ultrascale visualization ultravis, 2012. This concept is strongly related to the concept of graph degeneracy, which has a long history in graph theory. Free, secure and fast visualization software downloads from the largest open source applications and software directory.
In this paper, we construct a set of weighted software networks from realworld java software systems and empirically investigate their topological properties by using weighted kcore decomposition. The number of things most people can keep in working memory at one time is seven, plus or minus two. Topdown software decomposition an approach for componentbased design automation whitepaper ionut cardei department of computer science and engineering florida atlantic university boca raton, fl 33431 07212006 abstract in this whitepaper we summarize the objectives and the technical approach of. Software development for embedded multicore systems. May 20, 2009 the structures of largescale software systems are complex and difficult to understand for designers and developers. The kcore decomposition 4 consists in identifying particular subsets of the graph, called kcores, each one obtained by recursively removing. The structured analytic techniques toolbox geog 885. New release includes a free visualization function, plus new capabilities and improvements for virtual prediction and optimization for all casting processes, including continuous casting and core production. We have developped two new kinds of visualization, polar and ziggurat plots, based on k.
In this paper, we propose a visualization algorithm based on the k core decomposition able to uncover in a twodimensional layout several topological and hierarchical properties of large scale networks. One of its main applications is the study of the internet. This decomposition, based on a recursive pruning of the least connected vertices, allows to disentangle. In this paper we aim to explore whether k core decomposition of large networks can be computed using a consumergrade pc. We then place our implementations and experiments in this context. Following this are outofcore visualization experimental results, and some early remote outofcore visualization. Apr 28, 2005 we use the k core decomposition to visualize large scale complex networks in two dimensions. It is an acronym that stands for large networks visualization tool lanetvi is based on the kcore decomposition of a network. Each node of the core of order called shell has links with at least other nodes that belong to that same core. Software frameworks for visualization and analysis on nextgeneration multicore and manycore architectures.
In this paper, we propose a visualization algorithm based on the kcore decomposition able to uncover in a twodimensional layout several topological and hierarchical properties of large scale networks. We use the kcore decomposition to visualize large scale complex networks in two dimensions. We apply them to analyze maps obtained from the prominent internet mapping projects, using the lanetvi opensource software for its visualization. Above is an example of the digit 2, and the digit 3. Core decomposition has been shown to be an important concept in the study of graph properties and has many signi. In the k core decomposition problem, the goal is to compute the coreness of each vertex in g. New release includes a free visualization function, plus new capabilities and improvements for virtual prediction and optimization. An o m algorithm for cores decomposition of networks. Introduction nowadays, internet is a highly developed network connecting people. Pdf analyzing the structure of java software systems by. Understanding the properties enclosed in the weighted software networks can lead to better software engineering practices. Kcore decomposition of large networks on a single pc. Data visualization techniques, tools at core of advanced analytics data visualizations central role in advanced analytics applications includes uses in planning and developing predictive models as well as reporting on the analytical results they produce.
In other words, it is very difficult to do errorfree analysis only in our heads. Their internal structure is very important to understand their behaviour and resilience. Singular is a computer algebra system for polynomial computations, with special emphasis on commutative and noncommutative algebra, algebraic geometry, and singularity theory. Visualization of cracks by using the local voronoi. By using this strategy we develop a general visualization algorithm that can be used to compare the structural properties of various networks and highlight their hierarchical structure. Two new types of visualization for mutualistic communities. Large scale networks fingerprinting and visualization.
In this paper we aim to explore whether kcore decomposition of large networks can be computed using a consumergrade pc. The kcore is a well accepted concept partly because there exists a simple and. It allows users to define a chain of genomic filters, each of which perform on the output data provided by the previous filter, to filter reads out from sequencing data. The computing cluster is called tiger and has 36 cpu nodes. We use the k core decomposition to visualize large scale complex networks in two dimensions.
The kcore decomposition5 consists in identifying particular subsets of. The parallel speedup of the visualization software is investigated. Simply stated, the core decomposition of a network graph assigns to each graph node v, an integer number cv the core number, capturing how well v is connected with respect to its neighbors. Predicting binder decomposition and core gases foundry. Structured analysis breaks down a software system from the system context level to system functions and data entities as described by tom demarco. In reverse engineering, we aim to compute, for a given software system, a decomposition of the system into its subsystems. The core decomposition of networks has attracted significant attention due to its numerous applications in reallife problems. The superior performance of the applied local technique is compared to the performance observed by using the standard global voronoi algorithm. These all share the same software with a few rare exceptions. Taken alone, they do not constitute an analytic method for solving geospatial analytic problems.
Using the kcore decomposition to analyze the static structure of largescale software systems zhang, haohua, zhao, hai, cai, wei, liu, jie and zhou, wanlei 2010, using the kcore decomposition to analyze the static structure of largescale software systems, journal of supercomputing, vol. Kcore result page contains i mdl plugin, ii result table and iii amino acid details for each core. Introduction the unsteady flow analysis toolkit ufat software program is a pioneer tool for visualizing very large timedependent or unsteady flow data sets from computational fluid dynamics cfd simulations. Chemistry, visualization and related software in the mgcf. Download lanetvi large network visualization for free. This concept is strongly related to the concept of graph degeneracy.
Subroutines for computing partial singular value decompositions via randomized sampling on single core, multi core, and gpu architectures. Complexity increases geometrically as the number of variables increases. The display option is provided for each core to display the protein structure using mdl plugin. By using this strategy we develop a general visualization algorithm that can be used to compare the. The structured analytic techniques toolbox structured techniques are simply a box of tools to help the analyst mitigate the adverse impact on analysis of ones cognitive limitations and pitfalls. Understanding the structure of large existing and evolving software systems is a major challenge for software engineers. The structures of largescale software systems are complex and difficult to understand for designers and developers. Given a graph g,thekcore of g is the largest subgraph of gin which every vertex has degree of at leastkwithin the subgraph 1. Understanding edgeconnectivity in the internet through. Analyzing the structure of java software systems by weighted k core decomposition. Chemistry, visualization and related software in the mgcf the workstations in 175 tan hall are named. In this paper we use complex networks theory to study software structure. Heres a great example with using the first two terms of pca on the 2 and 3 digits from mnist.
Data visualization techniques, tools at core of advanced. For instance, it is quite important to know how central is a node and how its removal may trigger a cascade extinction 1. A metagenomic short read filtering software that uses a flexible configuration format. Compare the best free open source visualization software at sourceforge. The k core decomposition5 consists in identifying particular subsets of the graph, called kcores, each one obtained by. Understanding edgeconnectivity in the internet through core.
It is an acronym that stands for large networks visualization tool. It is free and opensource under the gnu general public licence. It can exploit sun grid engine and distribute individual processes. Although vtkm was born from a new code base, the piston, dax, and eavl developers con. The tool takes as input a variety of raw image data files and supports viewing of the data and a number of visual processing transformations. This decomposition, based on a recursive pruning of the least connected vertices, allows to disentangle the hierarchical structure of networks by progressively focusing on their central cores. The kcore is a well accepted concept partly because. We use the kcore decomposition to visualize large scale complex networks. In structured programming, algorithmic decomposition breaks a process down into welldefined steps. Lanetvi provides images of large scale networks on a twodimensional layout.
Analyzing the structure of java software systems by weighted kcore decomposition. The algorithm is based on the kcore and kdense mcore decomposition. Lanetvi is an opensource network visualization software. This concept is strongly related to the concept of graph. Amide is an open source tool that provides visualization of medical data. Following this are outof core visualization experimental results, and some early remote outof core visualization. There are different types of decomposition defined in computer sciences. Our software automatically harmonizes product and market data across all of the cpg syndicated and retail data sources, allowing customers to update their databases in minutes. In the kcore decomposition problem, the goal is to compute the coreness of each vertex in g. A k core of a graph is a maximal connected subgraph in which every vertex is connected to at least k vertices in the subgraph. Citeseerx scientific documents that cite the following paper. The k core decomposition 4 consists in identifying particular subsets of the graph, called kcores, each one obtained by recursively removing. It is released under the gnu general public license v3.
His current research focuses on outofcore algorithms and data structures for large graphics and visualization problems. Following this are outofcore visualization experimental results, and some early remote outofcore visualization experimental. This decomposition was introduced by seidman in 1983 and divides the network in layers the cores thus providing a centrality measure for nodes. Oct 06, 2016 data visualization techniques, tools at core of advanced analytics data visualization s central role in advanced analytics applications includes uses in planning and developing predictive models as well as reporting on the analytical results they produce. Using the kcore decomposition to analyze the static. Topdown software decomposition an approach for componentbased design automation whitepaper ionut cardei department of computer science and engineering florida atlantic university boca raton, fl 33431 07212006 abstract in this whitepaper we summarize the objectives and the technical approach of the top. As connectivity is a measure related to both of them partitions and selected paths this work provides a formal lower bound to it based on core decomposition, under certain conditions, and low complexity algorithms to find it. Ahern, a distributed dataparallel framework for analysis and visualization. A structural approach to disentangle the visualization of. Bedrocks sales decomposition tool is an easytoread sales breakdown, in which you can view sales performance by either dollar or unit volumes, which are then further dissected into base and incremental volumes. Streaming algorithms for kcore decomposition proceedings.
984 766 601 1109 707 354 1580 442 164 1461 549 158 804 1513 97 622 1310 1001 325 1171 723 899 760 1250 102 417 52 1238 1437 330 1047 44 1289 904 307 486 1052 129 177