A survey of direct methods for sparse linear systems
Wilkinson defined a sparse matrix as one with enough zeros that it pays to take advantage of
them. 1 This informal yet practical definition captures the essence of the goal of direct …
them. 1 This informal yet practical definition captures the essence of the goal of direct …
Productivity, performance, and portability for computational fluid dynamics applications
Hardware trends over the last decade show increasing complexity and heterogeneity in high
performance computing architectures, which presents developers of CFD applications with …
performance computing architectures, which presents developers of CFD applications with …
[BOOK][B] Algorithms for sparse linear systems
Large sparse linear systems of equations are ubiquitous in science, engineering and
beyond. This open access monograph focuses on factorization algorithms for solving such …
beyond. This open access monograph focuses on factorization algorithms for solving such …
GPU acceleration for FEM-based structural analysis
S Georgescu, P Chow, H Okuda - Archives of Computational Methods in …, 2013 - Springer
Abstract Graphic Processing Units (GPUs) have greatly exceeded their initial role of
graphics accelerators and have taken a new role of co-processors for computation—heavy …
graphics accelerators and have taken a new role of co-processors for computation—heavy …
Challenges in GPU-accelerated nonlinear dynamic analysis for structural systems
Many numerical simulation methods, such as finite-element analysis, were originally
formulated to run serially or in parallel on central processing units (CPUs). However …
formulated to run serially or in parallel on central processing units (CPUs). However …
Implementation and tuning of batched Cholesky factorization and solve for NVIDIA GPUs
Many problems in engineering and scientific computing require the solution of a large
number of small systems of linear equations. Due to their high processing power, Graphics …
number of small systems of linear equations. Due to their high processing power, Graphics …
A sparse symmetric indefinite direct solver for GPU architectures
In recent years, there has been considerable interest in the potential for graphics processing
units (GPUs) to speed up the performance of sparse direct linear solvers. Efforts have …
units (GPUs) to speed up the performance of sparse direct linear solvers. Efforts have …
Multifrontal QR factorization for multicore architectures over runtime systems
To face the advent of multicore processors and the ever increasing complexity of hardware
architectures, programming models based on DAG parallelism regained popularity in the …
architectures, programming models based on DAG parallelism regained popularity in the …
[HTML][HTML] Computational cost estimates for parallel shared memory isogeometric multi-frontal solvers
In this paper we present computational cost estimates for parallel shared memory
isogeometric multi-frontal solvers. The estimates show that the ideal isogeometric shared …
isogeometric multi-frontal solvers. The estimates show that the ideal isogeometric shared …
A parallel sparse direct solver via hierarchical DAG scheduling
K Kim, V Eijkhout - Acm transactions on mathematical software (toms), 2014 - dl.acm.org
We present a parallel sparse direct solver for multicore architectures based on Directed
Acyclic Graph (DAG) scheduling. Recently, DAG scheduling has become popular in …
Acyclic Graph (DAG) scheduling. Recently, DAG scheduling has become popular in …