Stencil computations form the heart of numerical simulations to solve Partial Differential Equations using Finite Difference, Finite Element, and Finite Volume methods. Geometric Multigrid is an optimal O(N), hierarchical tool employing stencil computations in its chief constituents, namely, smoothing, restriction, and interpolation. When Multigrid is parallelized over distributed‐shared memory architectures, traditionally, the domain partitioning creates cubic partitions of the mesh to minimize overall communication. Thus, the orthodox approach considers only load‐balancing and communication minimization for completely determining the domain partitioning. In this article, we show that these two factors are not sufficient to obtain optimal ...
We study the potential performance of multigrid algorithms running on massively parallel computers w...
In this work we propose a novel parallelization approach of two-level balancing domain decomposition...
New mapping algorithms for domain oriented data-parallel computations, where the workload is distrib...
Partial Differential Equations (PDEs) are used ubiquitously in modelling natural phenomena. It is ge...
In prior-research the authors have demonstrated that, for stencil-based numerical solvers for Partia...
Given a discretization stencil, partitioning the problem domain is an important first step for the e...
The algebraic multigrid (AMG) approach provides a purely algebraic means to tackle the efficient sol...
Geometric Multigrid (GMG) methods are widely used in numerical analysis to accelerate the convergenc...
AbstractThis paper addresses two key parallelization challenges the unstructured mesh-based ocean mo...
Many current computer designs employ caches and a hierarchical memory architecture. The speed of a c...
The partitioning of a problem on a domain with unequal work estimates in different subddomains is co...
The solution of elliptic partial differential equations is a common performance bottleneck in scient...
This paper describes a compiler transformation on stencil operators that automatically converts a st...
Summary. Multigrid methods are among the fastest numerical algorithms for the solution of large spar...
International audienceWe investigate the problem of partitioning finite difference meshes in two dim...
We study the potential performance of multigrid algorithms running on massively parallel computers w...
In this work we propose a novel parallelization approach of two-level balancing domain decomposition...
New mapping algorithms for domain oriented data-parallel computations, where the workload is distrib...
Partial Differential Equations (PDEs) are used ubiquitously in modelling natural phenomena. It is ge...
In prior-research the authors have demonstrated that, for stencil-based numerical solvers for Partia...
Given a discretization stencil, partitioning the problem domain is an important first step for the e...
The algebraic multigrid (AMG) approach provides a purely algebraic means to tackle the efficient sol...
Geometric Multigrid (GMG) methods are widely used in numerical analysis to accelerate the convergenc...
AbstractThis paper addresses two key parallelization challenges the unstructured mesh-based ocean mo...
Many current computer designs employ caches and a hierarchical memory architecture. The speed of a c...
The partitioning of a problem on a domain with unequal work estimates in different subddomains is co...
The solution of elliptic partial differential equations is a common performance bottleneck in scient...
This paper describes a compiler transformation on stencil operators that automatically converts a st...
Summary. Multigrid methods are among the fastest numerical algorithms for the solution of large spar...
International audienceWe investigate the problem of partitioning finite difference meshes in two dim...
We study the potential performance of multigrid algorithms running on massively parallel computers w...
In this work we propose a novel parallelization approach of two-level balancing domain decomposition...
New mapping algorithms for domain oriented data-parallel computations, where the workload is distrib...