The paper examines the parallel implementation of iteration type global illumination al-gorithms. 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
Asynchronous iterations arise naturally on parallel computers if one wants to minimize idle times. T...
The paper discusses the parallelization of Stochastic Evolution metaheuristic, identifying effective...
The main purpose of this work was to develop a more time efficient solution to the Lotka- Volterra m...
The paper examines the parallel implementation of iteration type global illumination al-gorithms. Th...
The paper examines the parallel implementation of iteration type global illumination algorithms. The...
textabstractThe global optimization problem, finding the lowest minimizer of a nonlinear function of...
This paper presents a single-pass, view-dependent method to solve the rendering equation, using a st...
This study addresses the stochastic optimization of a function unknown in closed form which can only...
This paper presents a stochastic iteration algorithm solving the global illumination problem, where ...
This paper discusses the parallelization of Stochastic Evolution (StocE) metaheuristic, for a distri...
International audienceIn this paper, we present some investigations on the parallelization of stocha...
Stochastic programming provides an effective framework for addressing decision prob-lems under uncer...
This paper investigates random number generators in stochastic iteration algorithms that require inf...
We develop scalable algorithms for two-stage stochastic program optimizations. We propose performanc...
This paper presents a stochastic iteration algorithm solving the global illumination problem, where ...
Asynchronous iterations arise naturally on parallel computers if one wants to minimize idle times. T...
The paper discusses the parallelization of Stochastic Evolution metaheuristic, identifying effective...
The main purpose of this work was to develop a more time efficient solution to the Lotka- Volterra m...
The paper examines the parallel implementation of iteration type global illumination al-gorithms. Th...
The paper examines the parallel implementation of iteration type global illumination algorithms. The...
textabstractThe global optimization problem, finding the lowest minimizer of a nonlinear function of...
This paper presents a single-pass, view-dependent method to solve the rendering equation, using a st...
This study addresses the stochastic optimization of a function unknown in closed form which can only...
This paper presents a stochastic iteration algorithm solving the global illumination problem, where ...
This paper discusses the parallelization of Stochastic Evolution (StocE) metaheuristic, for a distri...
International audienceIn this paper, we present some investigations on the parallelization of stocha...
Stochastic programming provides an effective framework for addressing decision prob-lems under uncer...
This paper investigates random number generators in stochastic iteration algorithms that require inf...
We develop scalable algorithms for two-stage stochastic program optimizations. We propose performanc...
This paper presents a stochastic iteration algorithm solving the global illumination problem, where ...
Asynchronous iterations arise naturally on parallel computers if one wants to minimize idle times. T...
The paper discusses the parallelization of Stochastic Evolution metaheuristic, identifying effective...
The main purpose of this work was to develop a more time efficient solution to the Lotka- Volterra m...