Abstract. The dynamism and space-time heterogeneity exhibited by structured adaptive mesh refinement (SAMR) applications makes their scalable parallel implementation a significant challenge. This paper investigates an adaptive hierarchical multi-partitioner (AHMP) framework that dynamically applies multiple partitioners to different regions of the domain, in a hierarchical manner, to match the local requirements of these regions. Key components of the AHMP framework include a segmentation-based clustering algorithm (SBC) for identifying regions in the domain with relatively homogeneous partitioning requirements, mechanisms for characterizing the partitioning requirements, and a runtime system for selecting, configuring and applying the most...
This paper presents a novel design and implementation of k-means clustering algorithm targeting the ...
International audienceRequirements for efficient parallelization of many complex and irregular appli...
We perform a comprehensive performance characterization of load balancing algorithms for parallel st...
Structured adaptive mesh refinement (SAMR) techniques provide an effective means for dynamically con...
Parallel structured adaptive mesh refinement methods decrease the execution time and memory usage of...
Abstract. This paper presents the design and experimental evaluation of two dynamic load partitionin...
We compare several different parallel implementation approaches for the clustering operations perfor...
Optimal partitioning of structured adaptive mesh applica-tions necessitates dynamically determining ...
Structured adaptive mesh refinement (SAMR) techniques can provide accurate and costeffective solutio...
Structured adaptive mesh refinement methods are being widely used for computer simulations of variou...
To increase the speed of computer simulations we solve partial differential equations (PDEs) using s...
The current state and foreseeable future of high performance scientific computing (HPC) can be descr...
Abstract. Hierarchical agglomerative clustering (HAC) is a common clustering method that outputs a d...
Dynamic adaptive mesh renement methods for the numerical solution to partial dierential equations yi...
Optimal partitioning of structured adaptive mesh applications necessitates dynamically determining a...
This paper presents a novel design and implementation of k-means clustering algorithm targeting the ...
International audienceRequirements for efficient parallelization of many complex and irregular appli...
We perform a comprehensive performance characterization of load balancing algorithms for parallel st...
Structured adaptive mesh refinement (SAMR) techniques provide an effective means for dynamically con...
Parallel structured adaptive mesh refinement methods decrease the execution time and memory usage of...
Abstract. This paper presents the design and experimental evaluation of two dynamic load partitionin...
We compare several different parallel implementation approaches for the clustering operations perfor...
Optimal partitioning of structured adaptive mesh applica-tions necessitates dynamically determining ...
Structured adaptive mesh refinement (SAMR) techniques can provide accurate and costeffective solutio...
Structured adaptive mesh refinement methods are being widely used for computer simulations of variou...
To increase the speed of computer simulations we solve partial differential equations (PDEs) using s...
The current state and foreseeable future of high performance scientific computing (HPC) can be descr...
Abstract. Hierarchical agglomerative clustering (HAC) is a common clustering method that outputs a d...
Dynamic adaptive mesh renement methods for the numerical solution to partial dierential equations yi...
Optimal partitioning of structured adaptive mesh applications necessitates dynamically determining a...
This paper presents a novel design and implementation of k-means clustering algorithm targeting the ...
International audienceRequirements for efficient parallelization of many complex and irregular appli...
We perform a comprehensive performance characterization of load balancing algorithms for parallel st...