Get to know two different techniques in retrieving parallelism hidden in a general purpose linear programs (LPs) that are broadly used in operations research, computer vision, and machine learning. With conventional solvers often being restricted to serial computation, we'll show two ways of retrieving inherent parallelism, using: (1) parallel sparse linear algebra techniques with an interior-point method, and (2) a higher-level automatic LP decomposition. After a quick introduction to the topic, we'll present details and results for a diverse range of applications on the GPU
Parallel computing research in the area of nonlinear optimization has been extremely intense during ...
This paper provides an introduction to algorithms for fundamental linear algebra problems on various...
Abstract—The simplex method is perhaps the most widely used method for solving linear programming (L...
Get to know two different techniques in retrieving parallelism hidden in a general purpose linear pr...
Graphics processing units (GPUs) are used as accelerators for algorithms in which the same instructi...
The increasing complexity of new parallel architectures has widened the gap between adaptability and...
In this paper we describe a unified algorithmic framework for the interior point method (IPM) of sol...
We survey general techniques and open problems in numerical linear algebra on parallel architectures...
This paper provides an introduction to algorithms for fundamental linear algebra problems on various...
International audienceThe increasing complexity of new parallel architectures has widened the gap be...
This study developed a parallel algorithm to efficiently solve linear programming models. The propos...
The original publication is available at www.springerlink.comInternational audienceA wide class of g...
In this review paper, we consider some important developments and trends in algorithm design for t...
Abstract In this document we present a new approach to developing sequential and parallel dense line...
International audienceIn this talk we will discuss our research activities on the design of parallel...
Parallel computing research in the area of nonlinear optimization has been extremely intense during ...
This paper provides an introduction to algorithms for fundamental linear algebra problems on various...
Abstract—The simplex method is perhaps the most widely used method for solving linear programming (L...
Get to know two different techniques in retrieving parallelism hidden in a general purpose linear pr...
Graphics processing units (GPUs) are used as accelerators for algorithms in which the same instructi...
The increasing complexity of new parallel architectures has widened the gap between adaptability and...
In this paper we describe a unified algorithmic framework for the interior point method (IPM) of sol...
We survey general techniques and open problems in numerical linear algebra on parallel architectures...
This paper provides an introduction to algorithms for fundamental linear algebra problems on various...
International audienceThe increasing complexity of new parallel architectures has widened the gap be...
This study developed a parallel algorithm to efficiently solve linear programming models. The propos...
The original publication is available at www.springerlink.comInternational audienceA wide class of g...
In this review paper, we consider some important developments and trends in algorithm design for t...
Abstract In this document we present a new approach to developing sequential and parallel dense line...
International audienceIn this talk we will discuss our research activities on the design of parallel...
Parallel computing research in the area of nonlinear optimization has been extremely intense during ...
This paper provides an introduction to algorithms for fundamental linear algebra problems on various...
Abstract—The simplex method is perhaps the most widely used method for solving linear programming (L...