Development and application of real-time and interactive software for complex system

Soft materials have attracted considerable interest in recent years for predicting the characteristics of phase separation and self-assembly in nanoscale structures. A popular method for demonstrating and simulating the dynamic behaviour of particles (e.g. particle tracking) and to consider effects of simulation parameters is cell dynamic simulation (CDS). This is a cellular computerisation technique that can be used to investigate different aspects of morphological topographies of soft material systems. The acquisition of quantitative data from particles is a critical requirement in order to obtain a better understanding and of characterising their dynamic behaviour. To achieve this objective particle tracking methods considering quantitative data and focusing on different properties and components of particles is essential. Despite the availability of various types of particle tracking used in experimental work, there is no method available to consider uniform computational data. In order to achieve accurate and efficient computational results for cell dynamic simulation method and particle tracking, two factors are essential: computing/calculating time-scale and simulation system size. Consequently, finding available computing algorithms and resources such as sequential algorithm for implementing a complex technique and achieving precise results is critical and rather expensive. Therefore, it is highly desirable to consider a parallel algorithm and programming model to solve time-consuming and massive computational processing issues. Hence, the gaps between the experimental and computational works and solving time consuming for expensive computational calculations need to be filled in order to investigate a uniform computational technique for particle tracking and significant enhancements in speed and execution times. The work presented in this thesis details a new particle tracking method for integrating diblock copolymers in the form of spheres with a shear flow and a novel designed GPU-based parallel acceleration approach to cell dynamic simulation (CDS). In addition, the evaluation of parallel models and architectures (CPUs and GPUs) utilising the mixtures of application program interface, OpenMP and programming model, CUDA were developed. Finally, this study presents the performance enhancements achieved with GPU-CUDA of approximately ~2 times faster than multi-threading implementation and 13~14 times quicker than optimised sequential processing for the CDS computations/workloads respectively

A parallel computing-visualization framework for polycrystalline minerals

In this report, we have reported some preliminary results in the development of a parallel computing-visualization framework for large-scale molecular dynamics simulations of polycrystals of minerals, which are geophysically relevant for Earth’s mantle. First, we have generated the input configurations of atoms belonging to various grains distributed in the space in a way, which resembles the polycrystalline structure of the minerals. The Input configuration is developed using Voronoi geometry. Thus generated polycrystalline system is simulated using the PolyCrystal Molecular Dynamics algorithm. Performance tests conducted using up to 256 processors and a couple of millions of atoms have shown that the computation time per MD step remains under 20 seconds. The other important part is the development of an efficient visualization system to interactively explore the massive three dimensional and time-dependent datasets produced by MD simulations. Some results are presented for the simulation of two-grain structure. The proposed framework is expected to be useful in simulations of more realistic and complex rheological (mechanical) properties of important Earth forming mineral phases under different conditions of stresses and temperatures

An Application Perspective on High-Performance Computing and Communications

We review possible and probable industrial applications of HPCC focusing on the software and hardware issues. Thirty-three separate categories are illustrated by detailed descriptions of five areas -- computational chemistry; Monte Carlo methods from physics to economics; manufacturing; and computational fluid dynamics; command and control; or crisis management; and multimedia services to client computers and settop boxes. The hardware varies from tightly-coupled parallel supercomputers to heterogeneous distributed systems. The software models span HPF and data parallelism, to distributed information systems and object/data flow parallelism on the Web. We find that in each case, it is reasonably clear that HPCC works in principle, and postulate that this knowledge can be used in a new generation of software infrastructure based on the WebWindows approach, and discussed in an accompanying paper

Designing a scalable dynamic load -balancing algorithm for pipelined single program multiple data applications on a non-dedicated heterogeneous network of workstations

Dynamic load balancing strategies have been shown to be the most critical part of an efficient implementation of various applications on large distributed computing systems. The need for dynamic load balancing strategies increases when the underlying hardware is a non-dedicated heterogeneous network of workstations (HNOW). This research focuses on the single program multiple data (SPMD) programming model as it has been extensively used in parallel programming for its simplicity and scalability in terms of computational power and memory size.;This dissertation formally defines and addresses the problem of designing a scalable dynamic load-balancing algorithm for pipelined SPMD applications on non-dedicated HNOW. During this process, the HNOW parameters, SPMD application characteristics, and load-balancing performance parameters are identified.;The dissertation presents a taxonomy that categorizes general load balancing algorithms and a methodology that facilitates creating new algorithms that can harness the HNOW computing power and still preserve the scalability of the SPMD application.;The dissertation devises a new algorithm, DLAH (Dynamic Load-balancing Algorithm for HNOW). DLAH is based on a modified diffusion technique, which incorporates the HNOW parameters. Analytical performance bound for the worst-case scenario of the diffusion technique has been derived.;The dissertation develops and utilizes an HNOW simulation model to conduct extensive simulations. These simulations were used to validate DLAH and compare its performance to related dynamic algorithms. The simulations results show that DLAH algorithm is scalable and performs well for both homogeneous and heterogeneous networks. Detailed sensitivity analysis was conducted to study the effects of key parameters on performance

Scalable parallel molecular dynamics algorithms for organic systems

A scalable parallel algorithm, Macro-Molecular Dynamics (MMD), has been developed for large-scale molecular dynamics simulations of organic macromolecules, based on space-time multi-resolution techniques and dynamic management of distributed lists. The algorithm also includes the calculation of long range forces using Fast Multipole Method (FMM). FMM is based on the octree data structure, in which each parent cell is divided into 8 child cells and this division continues until the cell size is equal to the non-bonded interaction cutoff length. Due to constant number of operations performed at each stage of the octree, the FMM algorithm scales as O(N). Design and analysis of MMD and FMM algorithms are presented. Scalability tests are performed on three tera-flop machines: 1024-processor Intel Xeon-based Linux cluster, SuperMike at LSU, 1184-processor IBM SP4 Marcellus and the 512-processor Compaq AlphaServer Emerald at the U.S. Army Engineer Research and Development Center (ERDC) MSRC. The tests show that the Linux cluster outperforms the SP4 for the MMD application. The tests also show significant effects of memory- and cache-sharing on the performance

Parallel molecular dynamics simulations of antimicrobial peptides

Molecular dynamics (MD) simulations of the wheat antimicrobial peptide â-purothionin were carried out in explicit water (~14,000 atoms) using an all-atom model. The structural properties of the peptide as a function of MD simulation, temperature, and presence of the mono- and divalent metal ions were investigated. The accuracy and scalability tests of the code Peach 3.8 for our system were performed on the Intel Xeon-based Linux cluster SuperHelix at Louisiana State University (LSU). The code showed the reliable accuracy and the parallel efficiency of 0.61 for ~14,000 particles on 16 processors. The microcanonical (MC) MD simulation of â-purothionin in water showed that all secondary structures were stable and exhibited normal conformation at 300 K initial temperature. Helicity of the peptide was found to depend strongly on temperature, consistent with experimental data. Analysis of the MD trajectories elucidated new details of temperature effects on purothionin. Thus, the á-helix á1 displayed unusual temperature resistance. The â-sheets and all four disulphide bonds were not affected by change in the range of temperature from 0 to 400 K. The residues Tyr13 and Arg30 thought to be involved in antimicrobial activity of purothionin displayed increased stability. Decrease in flexibility of the peptide largely decreased upon interaction with K+ and Mg 2+ ions. The MD simulations indicated that Mg2+ ions impaired the á-helix á2 and both ions interacted with Tyr13 and Agr30, suggesting the mechanism of cation inhibition for antimicrobial activity of purothionin. Therefore, the results reported here showed that the MC MD simulations reproduced effects of temperature and metal ions on structure of purothionin. Moreover, this study provided new insights into structural properties, and effects of temperature and metal ions on structure stability and conformation of the purothionin molecule

Software Support for Irregular and Loosely Synchronous Problems

A large class of scientific and engineering applications may be classified as irregular and loosely synchronous from the perspective of parallel processing. We present a partial classification of such problems. This classification has motivated us to enhance Fortran D to provide language support for irregular, loosely synchronous problems. We present techniques for parallelization of such problems in the context of Fortran D

Software Support for Irregular and Loosely Synchronous Problems

A large class of scientific and engineering applications may be classified as irregular and loosely synchronous from the perspective of parallel processing. We present a partial classification of such problems. This classification has motivated us to enhance Fortran D to provide language support for irregular, loosely synchronous problems. We present techniques for parallelization of such problems in the context of Fortran D