The Experts below are selected from a list of 948 Experts worldwide ranked by ideXlab platform
Helmar Burkhart - One of the best experts on this subject based on the ideXlab platform.
-
Reproducible Stencil compiler benchmarks using prova
Future Generation Computer Systems, 2019Co-Authors: Danilo Guerrera, Antonio Maffia, Helmar BurkhartAbstract:Abstract The Stencil Pattern represents a vast variety of applications, ranging from geophysics to medical science. In application codes, the Stencil kernel is often the part where most of the time is spent, thus forcing an efficient parallel implementation of it. On the other side, we know that Stencil computations are often memory-bound, which requires sophisticated parallelization techniques to get scalable solutions. In this paper, we present the results of Stencil benchmark experiments run on different systems using the prova! tool we are currently implementing. prova! aims for reproducible performance experiments and makes collaborative Stencil benchmarking feasible through web repositories and interfaces.
-
PMBS@SC - Reproducible Stencil compiler benchmarks using PROVA
2016Co-Authors: Danilo Guerrera, Helmar Burkhart, Antonio MaffiaAbstract:The Stencil Pattern represents a vast variety of applications, ranging from geophysics to medical science. In application codes, the Stencil kernel is often the part where most of the time is spent, thus forcing an efficient parallel implementation of it. On the other side we know that Stencil computations are often memory-bound, which requires sophisticated parallelization techniques to get scalable solutions.In this paper we present the results of a Stencil benchmark experiment run on two different systems by means of the PROVA! tool we are currently implementing. PROVA! aims for reproducible performance experiments and makes collaborative Stencil benchmarking feasible through web repositories and interfaces.
Danilo Guerrera - One of the best experts on this subject based on the ideXlab platform.
-
Reproducible Stencil compiler benchmarks using prova
Future Generation Computer Systems, 2019Co-Authors: Danilo Guerrera, Antonio Maffia, Helmar BurkhartAbstract:Abstract The Stencil Pattern represents a vast variety of applications, ranging from geophysics to medical science. In application codes, the Stencil kernel is often the part where most of the time is spent, thus forcing an efficient parallel implementation of it. On the other side, we know that Stencil computations are often memory-bound, which requires sophisticated parallelization techniques to get scalable solutions. In this paper, we present the results of Stencil benchmark experiments run on different systems using the prova! tool we are currently implementing. prova! aims for reproducible performance experiments and makes collaborative Stencil benchmarking feasible through web repositories and interfaces.
-
PMBS@SC - Reproducible Stencil compiler benchmarks using PROVA
2016Co-Authors: Danilo Guerrera, Helmar Burkhart, Antonio MaffiaAbstract:The Stencil Pattern represents a vast variety of applications, ranging from geophysics to medical science. In application codes, the Stencil kernel is often the part where most of the time is spent, thus forcing an efficient parallel implementation of it. On the other side we know that Stencil computations are often memory-bound, which requires sophisticated parallelization techniques to get scalable solutions.In this paper we present the results of a Stencil benchmark experiment run on two different systems by means of the PROVA! tool we are currently implementing. PROVA! aims for reproducible performance experiments and makes collaborative Stencil benchmarking feasible through web repositories and interfaces.
Jesper Larsson Träff - One of the best experts on this subject based on the ideXlab platform.
-
Efficient Process-to-Node Mapping Algorithms for Stencil Computations
arXiv: Distributed Parallel and Cluster Computing, 2020Co-Authors: Sascha Hunold, Konrad Von Kirchbach, Markus Lehr, Christian Schulz, Jesper Larsson TräffAbstract:Good process-to-compute-node mappings can be decisive for well performing HPC applications. A special, important class of process-to-node mapping problems is the problem of mapping processes that communicate in a sparse Stencil Pattern to Cartesian grids. By thoroughly exploiting the inherently present structure in this type of problem, we devise three novel distributed algorithms that are able to handle arbitrary Stencil communication Patterns effectively. We analyze the expected performance of our algorithms based on an abstract model of inter- and intra-node communication. An extensive experimental evaluation on several HPC machines shows that our algorithms are up to two orders of magnitude faster in running time than a (sequential) high-quality general graph mapping tool, while obtaining similar results in communication performance. Furthermore, our algorithms also achieve significantly better mapping quality compared to previous state-of-the-art Cartesian grid mapping algorithms. This results in up to a threefold performance improvement of an MPI_Neighbor_alltoall exchange operation. Our new algorithms can be used to implement the MPI_Cart_create functionality.
-
CLUSTER - Efficient Process-to-Node Mapping Algorithms for Stencil Computations
2020 IEEE International Conference on Cluster Computing (CLUSTER), 2020Co-Authors: Konrad Von Kirchbach, Sascha Hunold, Markus Lehr, Christian Schulz, Jesper Larsson TräffAbstract:Good process-to-compute-node mappings can be decisive for well performing HPC applications. A special, important class of process-to-node mapping problems is the problem of mapping processes that communicate in a sparse Stencil Pattern to Cartesian grids. By thoroughly exploiting the inherently present structure in this type of problem, we devise three novel distributed algorithms that are able to handle arbitrary Stencil communication Patterns effectively. We analyze the expected performance of our algorithms based on an abstract model of inter- and intra-node communication. An extensive experimental evaluation on several HPC machines shows that our algorithms are up to two orders of magnitude faster in running time than a (sequential) high-quality general graph mapping tool, while obtaining similar results in communication performance. Furthermore, our algorithms also achieve significantly better mapping quality compared to previous state-of-the-art Cartesian grid mapping algorithms. This results in up to a threefold performance improvement of an MPI_Neighbor_alltoall exchange operation. Our new algorithms can be used to implement the MPI_Cart_create functionality.
Antonio Maffia - One of the best experts on this subject based on the ideXlab platform.
-
Reproducible Stencil compiler benchmarks using prova
Future Generation Computer Systems, 2019Co-Authors: Danilo Guerrera, Antonio Maffia, Helmar BurkhartAbstract:Abstract The Stencil Pattern represents a vast variety of applications, ranging from geophysics to medical science. In application codes, the Stencil kernel is often the part where most of the time is spent, thus forcing an efficient parallel implementation of it. On the other side, we know that Stencil computations are often memory-bound, which requires sophisticated parallelization techniques to get scalable solutions. In this paper, we present the results of Stencil benchmark experiments run on different systems using the prova! tool we are currently implementing. prova! aims for reproducible performance experiments and makes collaborative Stencil benchmarking feasible through web repositories and interfaces.
-
PMBS@SC - Reproducible Stencil compiler benchmarks using PROVA
2016Co-Authors: Danilo Guerrera, Helmar Burkhart, Antonio MaffiaAbstract:The Stencil Pattern represents a vast variety of applications, ranging from geophysics to medical science. In application codes, the Stencil kernel is often the part where most of the time is spent, thus forcing an efficient parallel implementation of it. On the other side we know that Stencil computations are often memory-bound, which requires sophisticated parallelization techniques to get scalable solutions.In this paper we present the results of a Stencil benchmark experiment run on two different systems by means of the PROVA! tool we are currently implementing. PROVA! aims for reproducible performance experiments and makes collaborative Stencil benchmarking feasible through web repositories and interfaces.
Konrad Von Kirchbach - One of the best experts on this subject based on the ideXlab platform.
-
Efficient Process-to-Node Mapping Algorithms for Stencil Computations
arXiv: Distributed Parallel and Cluster Computing, 2020Co-Authors: Sascha Hunold, Konrad Von Kirchbach, Markus Lehr, Christian Schulz, Jesper Larsson TräffAbstract:Good process-to-compute-node mappings can be decisive for well performing HPC applications. A special, important class of process-to-node mapping problems is the problem of mapping processes that communicate in a sparse Stencil Pattern to Cartesian grids. By thoroughly exploiting the inherently present structure in this type of problem, we devise three novel distributed algorithms that are able to handle arbitrary Stencil communication Patterns effectively. We analyze the expected performance of our algorithms based on an abstract model of inter- and intra-node communication. An extensive experimental evaluation on several HPC machines shows that our algorithms are up to two orders of magnitude faster in running time than a (sequential) high-quality general graph mapping tool, while obtaining similar results in communication performance. Furthermore, our algorithms also achieve significantly better mapping quality compared to previous state-of-the-art Cartesian grid mapping algorithms. This results in up to a threefold performance improvement of an MPI_Neighbor_alltoall exchange operation. Our new algorithms can be used to implement the MPI_Cart_create functionality.
-
CLUSTER - Efficient Process-to-Node Mapping Algorithms for Stencil Computations
2020 IEEE International Conference on Cluster Computing (CLUSTER), 2020Co-Authors: Konrad Von Kirchbach, Sascha Hunold, Markus Lehr, Christian Schulz, Jesper Larsson TräffAbstract:Good process-to-compute-node mappings can be decisive for well performing HPC applications. A special, important class of process-to-node mapping problems is the problem of mapping processes that communicate in a sparse Stencil Pattern to Cartesian grids. By thoroughly exploiting the inherently present structure in this type of problem, we devise three novel distributed algorithms that are able to handle arbitrary Stencil communication Patterns effectively. We analyze the expected performance of our algorithms based on an abstract model of inter- and intra-node communication. An extensive experimental evaluation on several HPC machines shows that our algorithms are up to two orders of magnitude faster in running time than a (sequential) high-quality general graph mapping tool, while obtaining similar results in communication performance. Furthermore, our algorithms also achieve significantly better mapping quality compared to previous state-of-the-art Cartesian grid mapping algorithms. This results in up to a threefold performance improvement of an MPI_Neighbor_alltoall exchange operation. Our new algorithms can be used to implement the MPI_Cart_create functionality.