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arXiv2008

A Method for Solving Cyclic Block Penta-diagonal Systems of Linear Equations

A method for solving cyclic block three-diagonal systems of equations is generalized for solving a block cyclic penta-diagonal system of equations. Introducing a special form of two new variables the original system is split into three block pentagonal systems, which can be solved by the known methods. As such method belongs to class of direct methods without pivoting. Implementation of the algorithm is discussed in some details and the numerical examples are present.

cs.MS↗

arXiv2008

GraphStream: A Tool for bridging the gap between Complex Systems and Dynamic Graphs

The notion of complex systems is common to many domains, from Biology to Economy, Computer Science, Physics, etc. Often, these systems are made of sets of entities moving in an evolving environment. One of their major characteristics is the emergence of some global properties stemmed from local interactions between the entities themselves and between the entities and the environment. The structure of these systems as sets of interacting entities leads researchers to model them as graphs. However, their understanding requires most often to consider the dynamics of their evolution. It is indeed not relevant to study some properties out of any temporal consideration. Thus, dynamic graphs seem to be a very suitable model for investigating the emergence and the conservation of some properties. GraphStream is a Java-based library whose main purpose is to help researchers and developers in their daily tasks of dynamic problem modeling and of classical graph management tasks: creation, processing, display, etc. It may also be used, and is indeed already used, for teaching purpose. GraphStream relies on an event-based engine allowing several event sources. Events may be included in the core of the application, read from a file or received from an event handler.

cs.MS↗

arXiv2008

Conformal Computing: Algebraically connecting the hardware/software boundary using a uniform approach to high-performance computation for software and hardware applications

We present a systematic, algebraically based, design methodology for efficient implementation of computer programs optimized over multiple levels of the processor/memory and network hierarchy. Using a common formalism to describe the problem and the partitioning of data over processors and memory levels allows one to mathematically prove the efficiency and correctness of a given algorithm as measured in terms of a set of metrics (such as processor/network speeds, etc.). The approach allows the average programmer to achieve high-level optimizations similar to those used by compiler writers (e.g. the notion of "tiling"). The approach presented in this monograph makes use of A Mathematics of Arrays (MoA, Mullin 1988) and an indexing calculus (i.e. the psi-calculus) to enable the programmer to develop algorithms using high-level compiler-like optimizations through the ability to algebraically compose and reduce sequences of array operations. Extensive discussion and benchmark results are presented for the Fast Fourier Transform and other important algorithms.

cs.MS↗

arXiv2008

Algorithmic Based Fault Tolerance Applied to High Performance Computing

We present a new approach to fault tolerance for High Performance Computing system. Our approach is based on a careful adaptation of the Algorithmic Based Fault Tolerance technique (Huang and Abraham, 1984) to the need of parallel distributed computation. We obtain a strongly scalable mechanism for fault tolerance. We can also detect and correct errors (bit-flip) on the fly of a computation. To assess the viability of our approach, we have developed a fault tolerant matrix-matrix multiplication subroutine and we propose some models to predict its running time. Our parallel fault-tolerant matrix-matrix multiplication scores 1.4 TFLOPS on 484 processors (cluster jacquard.nersc.gov) and returns a correct result while one process failure has happened. This represents 65% of the machine peak efficiency and less than 12% overhead with respect to the fastest failure-free implementation. We predict (and have observed) that, as we increase the processor count, the overhead of the fault tolerance drops significantly.

cs.DC↗

arXiv2008

Revisiting the upper bounding process in a safe Branch and Bound algorithm

Finding feasible points for which the proof succeeds is a critical issue in safe Branch and Bound algorithms which handle continuous problems. In this paper, we introduce a new strategy to compute very accurate approximations of feasible points. This strategy takes advantage of the Newton method for under-constrained systems of equations and inequalities. More precisely, it exploits the optimal solution of a linear relaxation of the problem to compute efficiently a promising upper bound. First experiments on the Coconuts benchmarks demonstrate that this approach is very effective.

math.NA↗

arXiv2008

Executable Set Theory and Arithmetic Encodings in Prolog

The paper is organized as a self-contained literate Prolog program that implements elements of an executable finite set theory with focus on combinatorial generation and arithmetic encodings. The complete Prolog code is available at http://logic.csci.unt.edu/tarau/research/2008/pHFS.zip . First, ranking and unranking functions for some "mathematically elegant" data types in the universe of Hereditarily Finite Sets with Urelements are provided, resulting in arithmetic encodings for powersets, hypergraphs, ordinals and choice functions. After implementing a digraph representation of Hereditarily Finite Sets we define {\em decoration functions} that can recover well-founded sets from encodings of their associated acyclic digraphs. We conclude with an encoding of arbitrary digraphs and discuss a concept of duality induced by the set membership relation. In the process, we uncover the surprising possibility of internally sharing isomorphic objects, independently of their language level types and meanings.

cs.LO↗

arXiv2008

Ranking and Unranking of Hereditarily Finite Functions and Permutations

Prolog's ability to return multiple answers on backtracking provides an elegant mechanism to derive reversible encodings of combinatorial objects as Natural Numbers i.e. {\em ranking} and {\em unranking} functions. Starting from a generalization of Ackerman's encoding of Hereditarily Finite Sets with Urelements and a novel tupling/untupling operation, we derive encodings for Finite Functions and use them as building blocks for an executable theory of {\em Hereditarily Finite Functions}. The more difficult problem of {\em ranking} and {\em unranking} {\em Hereditarily Finite Permutations} is then tackled using Lehmer codes and factoradics. The paper is organized as a self-contained literate Prolog program available at \url{http://logic.csci.unt.edu/tarau/research/2008/pHFF.zip}

cs.LO↗

arXiv2008

A Functional Hitchhiker's Guide to Hereditarily Finite Sets, Ackermann Encodings and Pairing Functions

The paper is organized as a self-contained literate Haskell program that implements elements of an executable finite set theory with focus on combinatorial generation and arithmetic encodings. The code, tested under GHC 6.6.1, is available at http://logic.csci.unt.edu/tarau/research/2008/fSET.zip . We introduce ranking and unranking functions generalizing Ackermann's encoding to the universe of Hereditarily Finite Sets with Urelements. Then we build a lazy enumerator for Hereditarily Finite Sets with Urelements that matches the unranking function provided by the inverse of Ackermann's encoding and we describe functors between them resulting in arithmetic encodings for powersets, hypergraphs, ordinals and choice functions. After implementing a digraph representation of Hereditarily Finite Sets we define {\em decoration functions} that can recover well-founded sets from encodings of their associated acyclic digraphs. We conclude with an encoding of arbitrary digraphs and discuss a concept of duality induced by the set membership relation. Keywords: hereditarily finite sets, ranking and unranking functions, executable set theory, arithmetic encodings, Haskell data representations, functional programming and computational mathematics

cs.MS↗

arXiv2008

Parallel GPU Implementation of Iterative PCA Algorithms

Principal component analysis (PCA) is a key statistical technique for multivariate data analysis. For large data sets the common approach to PCA computation is based on the standard NIPALS-PCA algorithm, which unfortunately suffers from loss of orthogonality, and therefore its applicability is usually limited to the estimation of the first few components. Here we present an algorithm based on Gram-Schmidt orthogonalization (called GS-PCA), which eliminates this shortcoming of NIPALS-PCA. Also, we discuss the GPU (Graphics Processing Unit) parallel implementation of both NIPALS-PCA and GS-PCA algorithms. The numerical results show that the GPU parallel optimized versions, based on CUBLAS (NVIDIA) are substantially faster (up to 12 times) than the CPU optimized versions based on CBLAS (GNU Scientific Library).

q-bio.QM↗

arXiv2009

Geometric scaling: a simple preconditioner for certain linear systems with discontinuous coefficients

Linear systems with large differences between coefficients ("discontinuous coefficients") arise in many cases in which partial differential equations(PDEs) model physical phenomena involving heterogeneous media. The standard approach to solving such problems is to use domain decomposition techniques, with domain boundaries conforming to the boundaries between the different media. This approach can be difficult to implement when the geometry of the domain boundaries is complicated or the grid is unstructured. This work examines the simple preconditioning technique of scaling the equations by dividing each equation by the Lp-norm of its coefficients. This preconditioning is called geometric scaling (GS). It has long been known that diagonal scaling can be useful in improving convergence, but there is no study on the general usefulness of this approach for discontinuous coefficients. GS was tested on several nonsymmetric linear systems with discontinuous coefficients derived from convection-diffusion elliptic PDEs with small to moderate convection terms. It is shown that GS improved the convergence properties of restarted GMRES and Bi-CGSTAB, with and without the ILUT preconditioner. GS was also shown to improve the distribution of the eigenvalues by reducing their concentration around the origin very significantly.

cs.MS↗

arXiv2009

Bitslicing and the Method of Four Russians Over Larger Finite Fields

We present a method of computing with matrices over very small finite fields of size larger than 2. Specifically, we show how the Method of Four Russians can be efficiently adapted to these larger fields, and introduce a row-wise matrix compression scheme that both reduces memory requirements and allows one to vectorize element operations. We also present timings which confirm the efficiency of these methods and exceed the speed of the fastest implementations the authors are aware of.

cs.MS↗

arXiv2009

Rectangular Full Packed Format for Cholesky's Algorithm: Factorization, Solution and Inversion

We describe a new data format for storing triangular, symmetric, and Hermitian matrices called RFPF (Rectangular Full Packed Format). The standard two dimensional arrays of Fortran and C (also known as full format) that are used to represent triangular and symmetric matrices waste nearly half of the storage space but provide high performance via the use of Level 3 BLAS. Standard packed format arrays fully utilize storage (array space) but provide low performance as there is no Level 3 packed BLAS. We combine the good features of packed and full storage using RFPF to obtain high performance via using Level 3 BLAS as RFPF is a standard full format representation. Also, RFPF requires exactly the same minimal storage as packed format. Each LAPACK full and/or packed triangular, symmetric, and Hermitian routine becomes a single new RFPF routine based on eight possible data layouts of RFPF. This new RFPF routine usually consists of two calls to the corresponding LAPACK full format routine and two calls to Level 3 BLAS routines. This means {\it no} new software is required. As examples, we present LAPACK routines for Cholesky factorization, Cholesky solution and Cholesky inverse computation in RFPF to illustrate this new work and to describe its performance on several commonly used computer platforms. Performance of LAPACK full routines using RFPF versus LAPACK full routines using standard format for both serial and SMP parallel processing is about the same while using half the storage. Performance gains are roughly one to a factor of 43 for serial and one to a factor of 97 for SMP parallel times faster using vendor LAPACK full routines with RFPF than with using vendor and/or reference packed routines.

cs.MS↗

arXiv2009

On the bit-complexity of sparse polynomial multiplication

In this paper, we present fast algorithms for the product of two multivariate polynomials in sparse representation. The bit complexity of our algorithms are studied in detail for various types of coefficients, and we derive new complexity results for the power series multiplication in many variables. Our algorithms are implemented and freely available within the Mathemagix software. We show that their theoretical costs are well-reflected in practice.

cs.DS↗

arXiv2026

Compression with wildcards: All, or all maximum, anticlques of a graph

By definition an anticlique is an independent set of vertices of a graph $G$. By duality all results obtained for anticliques carry over to cliques. (It is for technical reasons that we stick with anticliques throughout.) We display the set $Acl(G)$ of all anticliques of $G$ in a compressed format that uses wildcards. Likewise (albeit less compressed) for the subfamily $MACL(G)\s Acl(G)$ of all maximum-cardinality members. The second task works particularly well for bipartite graphs (in fact for the broader class of König-Egarváry graphs). In this scenario Boolean functions (of type 2-CNF) will be important. Dilworth's lattice of all maximum antichains of a poset also features prominently.

cs.DS↗

arXiv2009

Automatic generation of non-uniform random variates for arbitrary pointwise computable probability densities by tiling

We present a rejection method based on recursive covering of the probability density function with equal tiles. The concept works for any probability density function that is pointwise computable or representable by tabular data. By the implicit construction of piecewise constant majorizing and minorizing functions that are arbitrarily close to the density function the production of random variates is arbitrarily independent of the computation of the density function and extremely fast. The method works unattended for probability densities with discontinuities (jumps and poles). The setup time is short, marginally independent of the shape of the probability density and linear in table size. Recently formulated requirements to a general and automatic non-uniform random number generator are topped. We give benchmarks together with a similar rejection method and with a transformation method.

cs.MS↗

arXiv2009

A Fast Multigrid Algorithm for Energy Minimization Under Planar Density Constraints

The two-dimensional layout optimization problem reinforced by the efficient space utilization demand has a wide spectrum of practical applications. Formulating the problem as a nonlinear minimization problem under planar equality and/or inequality density constraints, we present a linear time multigrid algorithm for solving correction to this problem. The method is demonstrated on various graph drawing (visualization) instances.

cs.DS↗

arXiv2009

The generating of Fractal Images Using MathCAD Program

This paper presents the graphic representation in the z-plane of the first three iterations of the algorithm that generates the Sierpinski Gasket. It analyzes the influence of the f(z) map when we represent fractal images.

cs.MS↗

arXiv2009

FISLAB - the Fuzzy Inference Tool-box for SCILAB

The present study represents "The Fislab package of programs meant to develop the fuzzy regulators in the Scilab environment" in which we present some general issues, usage requirements and the working mode of the Fislab environment. In the second part of the article some features of the Scilab functions from the Fislab package are described.

cs.MS↗