Jason A. Kraftcheck

An Interoperable, Data-Structure-Neutral Component for Mesh Query and Manipulation

Much of the effort required to create a new simulation code goes into developing infrastructure for mesh data manipulation, adaptive refinement, design optimization, and so forth. This infrastructure is an obvious target for code reuse, except that implementations of these functionalities are typically tied to specific data structures. In this article, we describe a software component---an abstract data model and programming interface---designed to provide low-level mesh query and manipulation support for meshing and solution algorithms. The component’s data model provides a data abstraction, completely hiding all details of how mesh data is stored, while its interface defines how applications can interact with that data. Because the component has been carefully designed to be general purpose and efficient, it provides a practical platform for implementing high-level mesh operations independently of the underlying mesh data structures. After describing the data model and interface, we provide several usage examples, each of which has been used successfully with multiple implementations of the interface functionality. The overhead due to accessing mesh data through the interface rather than directly accessing the underlying mesh data is shown to be acceptably small.

Mesh Interface Resolution and Ghost Exchange in a Parallel Mesh Representation

Algorithms are described for the resolution of shared vertices and higher-dimensional interfaces on domain-decomposed parallel mesh, and for ghost exchange between neighboring processors. Performance data is given for large (up to 64M tet and 32M hex element) meshes on up to 16k processors. Shared interface resolution for structured mesh is also described. Small modifications are required to enable the algorithm to match vertices based on geometric location, useful for joining multi-piece meshes, this capability is also demonstrated.

Interoperable mesh and geometry tools for advanced petascale simulations

SciDAC applications have a demonstrated need for advanced software tools to manage the complexities associated with sophisticated geometry, mesh, and field manipulation tasks, particularly as computer architectures move toward the petascale. The Center for Interoperable Technologies for Advanced Petascale Simulations (ITAPS) will deliver interoperable and interchangeable mesh, geometry, and field manipulation services that are of direct use to SciDAC applications. The premise of our technology development goal is to provide such services as libraries that can be used with minimal intrusion into application codes. To develop these technologies, we focus on defining a common data model and data-structure neutral interfaces that unify a number of different services such as mesh generation and improvement, front tracking, adaptive mesh refinement, shape optimization, and solution transfer operations. We highlight the use of several ITAPS services in SciDAC applications.

The TSTT Mesh Interface

PDE-based numerical simulation applications commonly use basic software infrastructure to manage mesh, geometry, and discretization data. The commonality of this infrastructure implies the software is theoretically amenable to re-use. However, the traditional reliance on library-based implementations of these functionalities hampers experimentation with different software instances that provide similar functionality. This is especially true for meshing and geometry libraries where applications often directly access the underlying data structures, which can be quite different from implementation to implementation. Thus, using different libraries interchangeably or interoperably for this functionality has proven difficult at best and has hampered the wide spread use of advanced meshing and geometry tools developed by the research community. To address these issues, the Terascale Simulation Tools and Technologies center is working to develop standard interfaces to enable the creation of interoperable and interchangeable simulation tools. In this paper, we focus on a languageand data-structure-independent interface supporting query and modification of mesh data conforming to a general abstract data model. We describe the model and interface, and provide programming “best practices” recommendations based on early experience implementing and using the interface.

Interoperable mesh components for large-scale, distributed-memory simulations

SciDAC applications have a demonstrated need for advanced software tools to manage the complexities associated with sophisticated geometry, mesh, and field manipulation tasks, particularly as computer architectures move toward the petascale. In this paper, we describe a software component – an abstract data model and programming interface – designed to provide support for parallel unstructured mesh operations. We describe key issues that must be addressed to successfully provide high-performance, distributed-memory unstructured mesh services and highlight some recent research accomplishments in developing new load balancing and MPI-based communication libraries appropriate for leadership class computing. Finally, we give examples of the use of parallel adaptive mesh modification in two SciDAC applications.

Interoperable geometry and mesh components for SciDAC applications

Software components for representing and evaluating geometry (TSTTG/CGM) and finite element mesh (TSTTM/MOAB), and a higher-level component for relations between the two (TSTTR/LASSO), have been combined with electromagnetic modelling and optimization techniques, to form a SciDAC shape optimization application. The TSTT data model described in this paper allows components involved in the shape optimization application to be coupled at a variety of levels, from coarse black-box coupling (e.g. to generate a model accelerator cavity using TSTTG) to very fine-grained coupling (e.g. smoothing individual mesh elements based in part on geometric surface normals at mesh vertices). Despite this flexibility, the TSTT data model uses only four fundamental data types (entities, sets, tags, and the interface object itself). We elaborate on the design and implementation of effective components in the context of this application, and show how our simple but flexible data model facilitates these efforts.