Methods and Distributed Software for Visualization of Cracks Propagating in Discrete Particle Systems

Scientific visualization is becoming increasingly important in analyzing and interpreting numerical and experimental data sets. Parallel computations of discrete particle systems lead to large data sets that can be produced, stored and visualized on distributed IT infrastructures. However, this leads to very complicated environments handling complex simulation and interactive visualization on the remote heterogeneous architectures. In micro-structure of continuum, broken connections between neighbouring particles can form complex cracks of unknown geometrical shape. The complex disjoint surfaces of cracks with holes and unavailability of a suitable scalar field defining the crack surfaces limit the application of the common surface extraction methods. The main visualization task is to extract the surfaces of cracks according to the connectivity of the broken connections and the geometry of the neighbouring particles. The research aims at enhancing the visualization methods of discrete particle systems and increasing speed of distributed visualization software. The dissertation consists of introduction, three main chapters and general conclusions. In the first Chapter, a literature review on visualization software, distributed environments, discrete element simulation of particle systems and crack visualization methods is presented. In the second Chapter, novel visualization methods were proposed for extraction of crack surfaces from monodispersed particle systems modelled by the discrete element method. The cell cut-based method, the Voronoi-based method and cell centre-based method explicitly define geometry of propagating cracks in fractured regions. The proposed visualization methods were implemented in the grid visualization e–service VizLitG and the distributed visualization software VisPartDEM. Partial data set transfer from the grid storage element was developed to reduce the data transfer and visualization time. In the third Chapter, the results of experimental research are presented. The performance of e-service VizLitG was evaluated in a geographically distributed grid. Different types of software were employed for data transfer in order to present the quantitative comparison. The performance of the developed visualization methods was investigated. The quantitative comparison of the execution time of local Voronoi-based method and that of global Voronoi diagrams generated by Voro++ library was presented. The accuracy of the developed methods was evaluated by computing the total depth of cuts made in particles by the extracted crack surfaces. The present research confirmed that the proposed visualization methods and the developed distributed software were capable of visualizing crack propagation modelled by the discrete element method in monodispersed particulate media

The Performance Analysis of the Thermal Discrete Element Method Computations on the GPU

The paper presents a GPU implementation of the thermal discrete element method (TDEM) and the comparative analysis of its performance. Several discrete element models for granular flows, the bonded particle model and the TDEM are considered for quantitative comparison of computational performance. The performance measured on NVIDIA(R) Tesla™ P100 GPU is compared with that attained by running the same OpenCL code on Intel(R) Xeon™ E5-2630 CPU with 20 cores. The presented GPU implementation of the TDEM increases the computing time of the bonded particle model only up to 30.6 % of the computing time of the simplest DEM model, which is an acceptable decrease in the performance required for solving coupled thermomechanical problems

Performance Evaluation of Parallel Haemodynamic Computations on Heterogeneous Clouds

The article presents performance evaluation of parallel haemodynamic flow computations on heterogeneous resources of the OpenStack cloud infrastructure. The main focus is on the parallel performance analysis, energy consumption and virtualization overhead of the developed software service based on ANSYS Fluent platform which runs on Docker containers of the private university cloud. The haemodynamic aortic valve flow described by incompressible Navier-Stokes equations is considered as a target application of the hosted cloud infrastructure. The parallel performance of the developed software service is assessed measuring the parallel speedup of computations carried out on virtualized heterogeneous resources. The performance measured on Docker containers is compared with that obtained by using the native hardware. The alternative solution algorithms are explored in terms of the parallel performance and power consumption. The investigation of a trade-off between the computing speed and the consumed energy is performed by using Pareto front analysis and a linear scalarization method

On Efficiency of Parallel Solvers for the Blood Flow through Aortic Valve

Mathematical modelling of cardiac haemodynamics presents a great challenge to the computational scientists due to numerous numerical issues and required computational resources. In this paper, we study the parallel performance of 3D simulation software for the blood flow through the aortic valve. The fluid flow problem with the open aortic valve leaflets is formulated and solved in parallel. The choice between the segregated and coupled numerical schemes is discussed and investigated. We present and compare the parallel performance results of both types of parallel solvers. We investigate their strong and weak scalability

Dam break flow simulation on grid

In this contribution we report on a dam break flow simulation on gLite based grid infrastructure. The dam break problem including breaking waves is solved by the pseudo-concentration method improved by interface sharpening technique. The developed interface sharpening procedure helps to preserve interface sharpness and mass conservation. The computed position of the leading edge of water column has been compared with the experimental measurements

Performance of Communication- and Computation-Intensive SaaS on the OpenStack Cloud

The pervasive use of cloud computing has led to many concerns, such as performance challenges in communication- and computation-intensive services on virtual cloud resources. Most evaluations of the infrastructural overhead are based on standard benchmarks. Therefore, the impact of communication issues and infrastructure services on the performance of parallel MPI-based computations remains unclear. This paper presents the performance analysis of communication- and computation-intensive software based on the discrete element method, which is deployed as a service (SaaS) on the OpenStack cloud. The performance measured on KVM-based virtual machines and Docker containers of the OpenStack cloud is compared with that obtained by using native hardware. The improved mapping of computations to multicore resources reduced the internode MPI communication by 34.4% and increased the parallel efficiency from 0.67 to 0.78, which shows the importance of communication issues. Increasing the number of parallel processes, the overhead of the cloud infrastructure increased to 13.7% and 11.2% of the software execution time on native hardware in the case of the Docker containers and KVM-based virtual machines of the OpenStack cloud, respectively. The observed overhead was mainly caused by OpenStack service processes that increased the load imbalance of parallel MPI-based SaaS

Performance analysis of cloud computing software services

The paper presents the performance analysis of the developed software as a service. In OpenStack cloud infrastructure, the software services for hemodynamic flow modelling and particle technology applications have been developed by using Apache jclouds API. The performance of the hosted cloud infrastructure has been assessed testing virtual memory, CPU, disk IO, network and the developed software services. The measured performance of the virtual OpenStack resources (full XEN virtualization) has been compared with that of the virtual Eucalyptus resources (KVM paravirtualization) and the native hardware. Article in Lithuanian. Debesų kompiuterijos programinės įrangos paslaugų greitaveikos tyrimai Santrauka Straipsnyje pristatomos sukurtos debesų kompiuterijos programinės įrangos paslaugos (SaaS) ir jų greitaveikos tyrimai. „OpenStack“ debesų kompiuterijos infrastruktūroje jclouds priemonėmis buvo sukurtos hemodinaminių srautų modeliavimo ir dalelių technologijų tyrimų diskrečiųjų elementų metodu programinės įrangos paslaugos. Debesų kompiuterijos infrastruktūros efektyvumas buvo ištirtas testuojant virtualios operatyviosios atmintinės, virtualaus CPU, virtualaus standžiojo disko, virtualaus tinklo ir sukurtų programinės įrangos paslaugų greitaveiką. Atliktas kiekybinis „OpenStack“ visos XEN virtualizacijos resursų greitaveikos palyginimas su „Eucalyptus“ KVM paravirtualizacijos resursų ir grynos aparatinės įrangos greitaveika. Reikšminiai žodžiai: debesų kompiuterija, programinės įrangos paslaugos, „OpenStack“, jclouds API, greitaveikos tyrimai

Efficient Visualization by Using ParaView Software on BalticGrid

The paper describes efficient visualization performed by using ParaView software on BalticGrid. Development efforts, software implementation details and grid deployment issues are presented. The benchmark based on visualization of poly-dispersed particle systems validates efficiency of the deployed software. Efficiency tests are performed on multi-core architecture. Data reading, glyph generation, CPU and GPU rendering is investigated and discussed

Performance evaluation of parallel haemodynamic computations on heterogeneous clouds

The article presents performance evaluation of parallel haemodynamic flow computations on heterogeneous resources of the OpenStack cloud infrastructure. The main focus is on the parallel performance analysis, energy consumption and virtualization overhead of the developed software service based on ANSYS Fluent platform, which runs on Docker containers of the private university cloud. The haemodynamic aortic valve flow described by incompressible Navier-Stokes equations is considered as a target application of the hosted cloud infrastructure. The parallel performance of the developed software service is assessed measuring the parallel speedup of computations carried out on virtualized heterogeneous resources. The performance measured on Docker containers is compared with that obtained by using the native hardware. The alternative solution algorithms are explored in terms of the parallel performance and power consumption. The investigation of a trade-off between the computing speed and the consumed energy is performed by using Pareto front analysis and a linear scalarization method