Existing partitioning algorithms provide limited support for load balancing simulations that are performed on heterogeneous parallel computing platforms. On such architectures, effective load balancing can only be achieved if the graph is distributed so that it properly takes into account the available resources (CPU speed, network bandwidth). With heterogeneous technologies becoming more popular, the need for suitable graph partitioning algorithms is critical. We developed such algorithms that can address the partitioning requirements of scientific computations, and can correctly model the architectural characteristics of emerging hardware platforms
Performance tuning of non-blocking threads is based on graph partitioning algorithms that create ser...
Heterogeneous platforms are mixes of different processing units in a compute node (e.g., CPUs+GPUs, ...
The current state and foreseeable future of high performance scientific computing (HPC) can be descr...
Existing partitioning algorithms provide limited support for load balancing simulations that are per...
Abstract Existing partitioning algorithms provide limited support for load balancing simulations tha...
This paper surveys graph partitioning algorithms used for parallel computing, with an emphasis on th...
International audienceGraph partitioning is a technique used for solving many problems in scientific...
International audienceGraph partitioning is a technique used for the solving of many problems in sci...
International audienceClassic load balancing is a major issue that determines the performance of par...
Load imbalance in an application can lead to degradation of performance and a significant drop in sy...
The graph partitioning problem is critical to many traditional applications such as work balancing ...
A method is outlined for optimising graph partitions which arise in mapping unstructured mesh calcul...
Calculations can naturally be described as graphs in which vertices represent computation and edges ...
Recently we proposed algorithms for concurrent execution on multiple clusters [11]. In this case, da...
Load balancing in large parallel systems with distributed memory is a difficult task often influenci...
Performance tuning of non-blocking threads is based on graph partitioning algorithms that create ser...
Heterogeneous platforms are mixes of different processing units in a compute node (e.g., CPUs+GPUs, ...
The current state and foreseeable future of high performance scientific computing (HPC) can be descr...
Existing partitioning algorithms provide limited support for load balancing simulations that are per...
Abstract Existing partitioning algorithms provide limited support for load balancing simulations tha...
This paper surveys graph partitioning algorithms used for parallel computing, with an emphasis on th...
International audienceGraph partitioning is a technique used for solving many problems in scientific...
International audienceGraph partitioning is a technique used for the solving of many problems in sci...
International audienceClassic load balancing is a major issue that determines the performance of par...
Load imbalance in an application can lead to degradation of performance and a significant drop in sy...
The graph partitioning problem is critical to many traditional applications such as work balancing ...
A method is outlined for optimising graph partitions which arise in mapping unstructured mesh calcul...
Calculations can naturally be described as graphs in which vertices represent computation and edges ...
Recently we proposed algorithms for concurrent execution on multiple clusters [11]. In this case, da...
Load balancing in large parallel systems with distributed memory is a difficult task often influenci...
Performance tuning of non-blocking threads is based on graph partitioning algorithms that create ser...
Heterogeneous platforms are mixes of different processing units in a compute node (e.g., CPUs+GPUs, ...
The current state and foreseeable future of high performance scientific computing (HPC) can be descr...