The paper examines the parallel implementation of iteration type global illumination algorithms. The steps of iteration depend on each other, thus their parallel implementation is not as straightforward as for random walks. This paper solves the interdependency problem by applying stochastic iteration. In this framework two fundamental questions are investigated: how many processors can be efficiently used in an algorithm and how often the processors should exchange their information. These questions are answered by a theoretical model and also by simulations
Stochastic programming provides an effective framework for addressing decision prob-lems under uncer...
The paper discusses the parallelization of Stochastic Evolution metaheuristic, identifying effective...
We study different parallelization schemes for the stochastic dual dynamic programming (SDDP) algori...
The paper examines the parallel implementation of iteration type global illumination al-gorithms. Th...
This paper presents a single-pass, view-dependent method to solve the rendering equation, using a st...
textabstractThe global optimization problem, finding the lowest minimizer of a nonlinear function of...
This study addresses the stochastic optimization of a function unknown in closed form which can only...
In computer graphics, global illumination algorithms take into account not only the light that comes...
This paper investigates random number generators in stochastic iteration algorithms that require inf...
This paper discusses the parallelization of Stochastic Evolution (StocE) metaheuristic, for a distri...
The main purpose of this work was to develop a more time efficient solution to the Lotka- Volterra m...
International audienceIn this paper, we present some investigations on the parallelization of stocha...
Asynchronous iterations arise naturally on parallel computers if one wants to minimize idle times. T...
SIGLEAvailable from British Library Document Supply Centre- DSC:8717.57(HP-NOC-TR--221) / BLDSC - Br...
We develop scalable algorithms for two-stage stochastic program optimizations. We propose performanc...
Stochastic programming provides an effective framework for addressing decision prob-lems under uncer...
The paper discusses the parallelization of Stochastic Evolution metaheuristic, identifying effective...
We study different parallelization schemes for the stochastic dual dynamic programming (SDDP) algori...
The paper examines the parallel implementation of iteration type global illumination al-gorithms. Th...
This paper presents a single-pass, view-dependent method to solve the rendering equation, using a st...
textabstractThe global optimization problem, finding the lowest minimizer of a nonlinear function of...
This study addresses the stochastic optimization of a function unknown in closed form which can only...
In computer graphics, global illumination algorithms take into account not only the light that comes...
This paper investigates random number generators in stochastic iteration algorithms that require inf...
This paper discusses the parallelization of Stochastic Evolution (StocE) metaheuristic, for a distri...
The main purpose of this work was to develop a more time efficient solution to the Lotka- Volterra m...
International audienceIn this paper, we present some investigations on the parallelization of stocha...
Asynchronous iterations arise naturally on parallel computers if one wants to minimize idle times. T...
SIGLEAvailable from British Library Document Supply Centre- DSC:8717.57(HP-NOC-TR--221) / BLDSC - Br...
We develop scalable algorithms for two-stage stochastic program optimizations. We propose performanc...
Stochastic programming provides an effective framework for addressing decision prob-lems under uncer...
The paper discusses the parallelization of Stochastic Evolution metaheuristic, identifying effective...
We study different parallelization schemes for the stochastic dual dynamic programming (SDDP) algori...