Mesh partitioning: A multilevel balancing and refinement algorithm

Multilevel algorithms are a successful class of optimisation techniques which address the mesh partitioning problem. They usually combine a graph contraction algorithm together with a local optimisation method which refines the partition at each graph level. In this paper we present an enhancement of the technique which uses imbalance to achieve higher quality partitions. We also present a formulation of the Kernighan-Lin partition optimisation algorithm which incorporates load-balancing. The resulting algorithm is tested against a different but related state-of the-art partitioner and shown to provide improved results.

Multilevel mesh partitioning for optimising domain shape

Multilevel algorithms are a successful class of optimisation techniques which address the mesh partitioning problem for mapping meshes onto parallel computers. They usually combine a graph contraction algorithm together with a local optimisation method which refines the partition at each graph level. To date these algorithms have been used almost exclusively to minimise the cut-edge weight in the graph with the aim of minimising the parallel communication overhead. However it has been shown that for certain classes of problem, the convergence of the underlying solution algorithm is strongly influenced by the shape or aspect ratio of the subdomains. In this paper therefore, we modify the multilevel algorithms in order to optimise a cost function based on aspect ratio. Several variants of the algorithms are tested and shown to provide excellent results.

Parallel optimisation algorithms for multilevel mesh partitioning

Abstract not available

Multiphase mesh partitioning

Abstract not available

Automatic generation of portable multi-dimensionally decomposed parallel structured mesh software

Abstract not available

Computer aided parallelisation of unstructured mesh codes

Abstract not available

Evaluation of the JOSTLE mesh partitioning code for practical multiphysics applications

The use of unstructured mesh codes on parallel machines is one of the most effective ways to solve large computational mechanics problems. Completely general geometries and complex behaviour can be modelled and, in principle, the inherent sparsity of many such problems can be exploited to obtain excellent parallel efficiencies. However, unlike their structured counterparts, the problem of distributing the mesh across the memory of the machine, whilst minimising the amount of interprocessor communication, must be carefully addressed. This process is an overhead that is not incurred by a serial code, but is shown to rapidly computable at turn time and tailored for the machine being used.

Semi-automatic parallelisation of unstructured mesh codes

The availability of CFD software that can easily be used and produce high efficiency on a wide range of parallel computers is extremely limited. The investment and expertise required to parallelise a code can be enormous. In addition, the cost of supercomputers forces high utilisation to justify their purchase, requiring a wide range of software. To break this impasse, tools are urgently required to assist in the parallelisation process that dramatically reduce the parallelisation time but do not degrade the performance of the resulting parallel software. In this paper we discuss enhancements to the Computer Aided Parallelisation Tools (CAPTools) to assist in the parallelisation of complex unstructured mesh-based computational mechanics codes.

Multiphysics modelling of materials processing using finite volume unstructured mesh procedures

Abstract not available

Multilevel mesh partitioning for optimising subdomain aspect ratio

Multilevel algorithms are a successful class of optimisation techniques which address the mesh partitioning problem for mapping meshes onto parallel computers. They usually combine a graph contraction algorithm together with a local optimisation method which refines the partition at each graph level. To date these algorithms have been used almost exclusively to minimise the cut-edge weight in the graph with the aim of minimising the parallel communication overhead. However it has been shown that for certain classes of problem, the convergence of the underlying solution algorithm is strongly influenced by the shape or aspect ratio of the subdomains. In this paper therefore, we modify the multilevel algorithms in order to optimise a cost function based on aspect ratio. Several variants of the algorithms are tested and shown to provide excellent results.

Partition alignment in three dimensional unstructured mesh multi-physics modelling

Unstructured mesh codes for modelling continuum physics phenomena have evolved to provide the facility to model complex interacting systems. Parallelisation of such codes using single Program Multi Data (SPMD) domain decomposition techniques implemented with message passing has been demonstrated to provide high parallel efficiency, scalability to large numbers of processors P and portability across a wide range of parallel platforms. High efficiency, especially for large P requires that load balance is achieved in each parallel loop. For a code in which loops span a variety of mesh entity types, for example, elements, faces and vertices, some compromise is required between load balance for each entity type and the quantity of inter-processor communication required to satisfy data dependence between processors.

Multilevel mesh partitioning for aspect ratio

Multilevel algorithms are a successful class of optimisation techniques which address the mesh partitioning problem. They usually combine a graph contraction algorithm together with a local optimisation method which refines the partition at each graph level. To date these algorithms have been used almost exclusively to minimise the cut-edge weight, however it has been shown that for certain classes of solution algorithm, the convergence of the solver is strongly influenced by the subdomain aspect ratio. In this paper therefore, we modify the multilevel algorithms in order to optimise a cost function based on aspect ratio. Several variants of the algorithms are tested and shown to provide excellent results.

Scalable unstructured mesh decomposition

As the efficiency of parallel software increases it is becoming common to measure near linear speedup for many applications. For a problem size N on P processors then with software running at O(N=P ) the performance restrictions due to file i/o systems and mesh decomposition running at O(N) become increasingly apparent especially for large P . For distributed memory parallel systems an additional limit to scalability results from the finite memory size available for i/o scatter/gather operations. Simple strategies developed to address the scalability of scatter/gather operations for unstructured mesh based applications have been extended to provide scalable mesh decomposition through the development of a parallel graph partitioning code, JOSTLE [8]. The focus of this work is directed towards the development of generic strategies that can be incorporated into the Computer Aided Parallelisation Tools (CAPTools) project.

Aspect ratio for mesh partitioning

This paper deals with the measure of Aspect Ratio for mesh partitioning and gives hints why, for certain solvers, the Aspect Ratio of partitions plays an important role. We define and rate different kinds of Aspect Ratio, present a new center-based partitioning method which optimizes this measure implicitly and rate several existing partitioning methods and tools under the criterion of Aspect Ratio.

Mesh partitioning and load balancing for distributed memory parallel systems

A method is outlined for optimising graph partitions which arise in mapping unstructured mesh calculations to parallel computers. The method employs a relative gain iterative technique to both evenly balance the workload and minimise the number and volume of interprocessor communications. A parallel graph reduction technique is also briefly described and can be used to give a global perspective to the optimisation. The algorithms work efficiently in parallel as well as sequentially and when combined with a fast direct partitioning technique (such as the Greedy algorithm) to give an initial partition, the resulting two-stage process proves itself to be both a powerful and flexible solution to the static graph-partitioning problem. Experiments indicate that the resulting parallel code can provide high quality partitions, independent of the initial partition, within a few seconds. The algorithms can also be used for dynamic load-balancing, reusing existing partitions and in this case the procedures are much faster than static techniques, provide partitions of similar or higher quality and, in comparison, involve the migration of a fraction of the data.