Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Fast parallel algorithms for short-range molecular dynamics

Overview of constitutive laws, kinematics, homogenization and multiscale methods in crystal plasticity finite-element modeling: Theory, experiments, applications

By L I Sedov London: Cleaver-Hume Press Ltd Pp xvi + 363 Price 105s This is really two separate books within the same pair of covers First of all Chapters 1-3, some 145 pages, are devoted to the discussion of similarity and dimensional, methods and their application to a variety of problems in mechanics and fluid mechanics

http://iopscience.iop.org/article/10.1088/0031-9112/11/6/008/pdf

Similarity and Dimensional Methods in Mechanics

An adaptive, formally second order accurate version of the immersed boundary method

Immersed boundary methods for simulating fluid-structure interaction

A major challenge facing software libraries for scientific computing is the ability to provide adequate flexibility to meet sophisticated, diverse, and evolving application requirements. Object-oriented design techniques are valuable tools for capturing characteristics of complex applications in a software architecture. In this paper, we describe certain prominent object-oriented features of the SAMRAI software library that have proven to be useful in application development. SAMRAI is used in a variety of applications and has demonstrated a substantial amount of code and design re-use in those applications. This flexibility and extensibility is illustrated with three different application codes. We emphasize two important features of our design. First, we describe the composition of complex numerical algorithms from smaller components which are usable in different applications. Second, we discuss the extension of existing framework components to satisfy new application needs. Published in 2002 by John Wiley & Sons, Ltd.

Managing application complexity in the SAMRAI object‐oriented framework

The RAJA Portability Layer: Overview and Status

Adaptive mesh refinement (AMR) is an increasingly important simulation methodology for many science and engineering problems. AMR has the potential to generate highly resolved simulations efficiently by dynamically refining the computational mesh near key numerical solution features. AMR requires more complex numerical algorithms and programming than uniform fixed mesh approaches. Software libraries that provide general AMR functionality can ease these burdens significantly. A major challenge for library developers is to achieve adequate flexibility to meet diverse and evolving application requirements. In this paper, we describe the design of software abstractions for general AMR data management and parallel communication operations in SAMRAI, an object-oriented C++ structured AMR (SAMR) library developed at Lawrence Livermore National Laboratory (LLNL). The SAMRAI infrastructure provides the foundation for a variety of diverse application codes at LLNL and elsewhere. We illustrate SAMRAI functionality by describing how its unique features are used in these codes which employ complex data structures and geometry. We highlight capabilities for moving and deforming meshes, coupling multiple SAMR mesh hierarchies, and immersed and embedded boundary methods for modeling complex geometrical features. We also describe how irregular data structures, such as particles and internal mesh boundaries, may be implemented using SAMRAI tools without excessive application programmer effort.

Managing complex data and geometry in parallel structured AMR applications

This paper discusses the design and performance of the parallel data communication infrastructure in SAMRAI, a software framework for structured adaptive mesh refinement (SAMR) multi-physics applications. We describe requirements of such applications and how SAMRAI abstractions manage complex data communication operations found in them. Parallel performance is characterized for two adaptive problems solving hyperbolic conservation laws on up to 512 processors of the IBM ASCI Blue Pacific system. Results reveal good scaling for numerical and data communication operations but poorer scaling in adaptive meshing and communication schedule construction phases of the calculations. We analyze the costs of these different operations, addressing key concerns for scaling SAMR computations to large numbers of processors, and discuss potential changes to improve our current implementation.

/pdf/large-scale-parallel-structured-amr-calculations-using-the-56gkngg81r.pdf

Richard D. Hornung

Papers

An adaptive, formally second order accurate version of the immersed boundary method

Managing application complexity in the SAMRAI object‐oriented framework

The RAJA Portability Layer: Overview and Status

Managing complex data and geometry in parallel structured AMR applications

Large Scale Parallel Structured AMR Calculations Using the SAMRAI Framework