Multiple peak alignment in sequential data analysis : a scale-space-based approach (2006)
Yu, Weichuan, Li, Xiaoye, Liu, Junfeng, Wu, Baolin, Williams, Kenneth R., Zhao, Hongyu
In this paper, we address the multiple peak alignment problem in sequential data analysis with an approach based on the Gaussian scale-space theory. We assume that multiple sets of detected peaks are...
Algebraic sub-structuring for electromagnetic applications (2004)
Yang, Chao, Gao, Weiguo, Bai, Zhaojun, Li, Xiaoye, Lee, Lie-Quan, Husbands, Parry, ...
Algebraic sub-structuring refers to the process of applying matrix reordering and partitioning algorithms to divide a large sparse matrix into smaller submatrices from which a subset of spectral...
Leonid Oliker, Xiaoye Li, Parry Husbands, Rupak Biswas
Theconjuga#8 gra#uga t (CG)a#G).K--1; is perha#8 the best-knownitera#55 e technique for solvingspa#in linea# systemstha# a#a symmetrica#m positive definite.For systemstha# a#a ill conditioned, it is...
A complete description of two outgoing electrons following an ionizing collision between a single electron and an atom or molecule has long stood as one of the unsolved fundamental problems in...
Effects of Ordering Strategies and Programming Paradigms on Sparse Matrix Computations (2001)
Leonid Oliker, Xiaoye Li, Parry Husbands, Rupak Biswas
. The Conjugate Gradient (CG) algorithm is perhaps the best-known iterative technique to solve sparse linear systems that are symmetric and positive definite. For systems that are ill-conditioned, it...
Ordering Schemes for Sparse Matrices using Modern Programming Paradigms (2001)
Leonid Oliker, Xiaoye Li, Parry Husbands, Rupak Biswas
The Conjugate Gradient (CG) algorithm is perhaps the best-known iterative technique to solve sparse linear systems that are symmetric and positive definite. In previous work, we investigated the...
Ordering schemes for sparse matrices using modern programming paradigms (2000)
Oliker, Leonid, Li, Xiaoye, Husbands, Parry, Biswas, Rupak
The Conjugate Gradient (CG) algorithm is perhaps the best-known iterative technique to solve sparse linear systems that are symmetric and positive definite. In previous work, we investigated the...
Leonid Oliker, Xiaoye Li, Gerd Heber, Rupak Biswas
The Conjugate Gradient (CG) algorithm is perhaps the best-known iterative technique to solve sparse linear systems that are symmetric and positive definite. A sparse matrix-vector multiply (SPMV)...
Ordering Unstructured Meshes for Sparse Matrix Computations on Leading Parallel Systems (2000)
Leonid Oliker, Xiaoye Li, Gerd Heber, Rupak Biswas
. Computer simulations of realistic applications usually require solving a set of non-linear partial differential equations (PDEs) over a finite region. The process of obtaining numerical solutions...
Ordering Unstructured Meshes for Sparse Matrix Computations on Leading Parallel Systems (1999)
Leonid Oliker, Xiaoye Li, Gerd Heber
this paper, we focus on the efficiency of SPMV using various ordering/partitioning algorithms. We examine different implementations using three leading programming paradigms and architectures....
A Reference Implementation for Extended and Mixed Precision BLAS (1999)
James Demmel, Xiaoye Li, David Bailey, Michael Martin, Jimmy Iskandar, Anil Kapur
This paper describes a C implementation of the proposed new BLAS Standard. Permitting mixtures of input/output types and precisions, as well as higher internal precision, the new BLAS standard...
Faster Numerical Algorithms via Exception Handling (1998)
An attractive paradigm for building fast numerical algorithms is the following: (1) try a fast but occasionally unstable algorithm, (2) test the accuracy of the computed answer, and (3) recompute the...
Data-level Parallel Solution of Min-cost Network Flow Problems Using (1998)
this report is restricted to network flow problems.
Sparse Gaussian elimination on high performance computers / (1996)
Abstract: "This dissertation presents new techniques for solving large sparse unsymmetric linear systems on high performance computers, using Gaussian elimination with partial pivoting. The...
Data-level Parallel Solution of Min-cost Network Flow Problems Using epsilon-Relaxations (1995)
this report is restricted to network flow problems. Several classes of nonlinear network optimization problems have benefited from the design and implementation of massively parallel algorithms. For...
Faster Numerical Algorithms via Exception Handling (1995)
An attractive paradigm for building fast numerical algorithms is the following: (1) try a fast but occasionally unstable algorithm, (2) test the accuracy of the computed answer, and (3) recompute the...