Add to ORKGIn this paper we propose and solve common influence region queries. We present GPU parallel algorithms, designed under CUDA architecture, for approximately solving the studied queries. We also provide and discuss experimental results showing the efficiency of our approach.Ministerio de Ciencia e Innovació
International audienceLocal search algorithms are powerful heuristics for solving computationally ha...
Graphics processor units (GPUs) are many-core processors that perform better than central processing...
We present a multi-purpose genetic algorithm, designed and implemented with GPGPU / CUDA parallel co...
In this paper we propose and solve common influence region problems. These problems are related to t...
In this paper we study a problem that arises in the competitive facility location field. Facilities ...
In this paper we present how recent hardware revisions and newly introduced approaches to thread col...
Abstract. During the last few years, Graphics Processing Units (GPU) have evolved from simple device...
Every new desktop or laptop come equipped with a multicore, programmable graphic processing unit (GP...
Nearest neighbor analysis is one of the classic methods to find out the tendency of the observed poi...
The parallel computing power offered by graphic processing units (GPUs) has been recently exploited ...
In 2006 NVIDIA introduced a new unified GPU architecture facilitating general-purpose computation on...
A crescente disponibilidade de dados em diferentes domínios tem motivado o desenvolvimento de técnic...
CUDA is a parallel programming environment that enables significant performance improvement by lever...
In this paper we present an efficient and general sorting-based approach for the neighbor search on ...
Now a days there are different number of optimization problems are present. Which are NP problems to...
International audienceLocal search algorithms are powerful heuristics for solving computationally ha...
Graphics processor units (GPUs) are many-core processors that perform better than central processing...
We present a multi-purpose genetic algorithm, designed and implemented with GPGPU / CUDA parallel co...
In this paper we propose and solve common influence region problems. These problems are related to t...
In this paper we study a problem that arises in the competitive facility location field. Facilities ...
In this paper we present how recent hardware revisions and newly introduced approaches to thread col...
Abstract. During the last few years, Graphics Processing Units (GPU) have evolved from simple device...
Every new desktop or laptop come equipped with a multicore, programmable graphic processing unit (GP...
Nearest neighbor analysis is one of the classic methods to find out the tendency of the observed poi...
The parallel computing power offered by graphic processing units (GPUs) has been recently exploited ...
In 2006 NVIDIA introduced a new unified GPU architecture facilitating general-purpose computation on...
A crescente disponibilidade de dados em diferentes domínios tem motivado o desenvolvimento de técnic...
CUDA is a parallel programming environment that enables significant performance improvement by lever...
In this paper we present an efficient and general sorting-based approach for the neighbor search on ...
Now a days there are different number of optimization problems are present. Which are NP problems to...
International audienceLocal search algorithms are powerful heuristics for solving computationally ha...
Graphics processor units (GPUs) are many-core processors that perform better than central processing...
We present a multi-purpose genetic algorithm, designed and implemented with GPGPU / CUDA parallel co...