Alvaro L. G. A. Coutinho

High Performance Computing for Computational Science - VECPAR 2006

1: Grid Computing.- An Opportunistic Algorithm for Scheduling Workflows on Grids.- A Service Oriented System for on Demand Dynamic Structural Analysis over Computational Grids.- Scalable Desktop Grid System.- Analyzing Overheads and Scalability Characteristics of OpenMP Applications.- Parallel Fuzzy c-Means Cluster Analysis.- Peer-to-Peer Models for Resource Discovery in Large-Scale Grids: A Scalable Architecture.- 2: Cluster Computing.- JaceV: A Programming and Execution Environment for Asynchronous Iterative Computations on Volatile Nodes.- Aspect Oriented Pluggable Support for Parallel Computing.- Model for Simulation of Heterogeneous High-Performance Computing Environments.- On Evaluating Decentralized Parallel I/O Scheduling Strategies for Parallel File Systems.- Distributed Security Constrained Optimal Power Flow Integrated to a DSM Based Energy Management System for Real Time Power Systems Security Control.- Metaserver Locality and Scalability in a Distributed NFS.- Top-k Query Processing in the APPA P2P System.- Posterior Task Scheduling Algorithms for Heterogeneous Computing Systems.- Design and Implementation of an Environment for Component-Based Parallel Programming.- Anahy: A Programming Environment for Cluster Computing.- DWMiner: A Tool for Mining Frequent Item Sets Efficiently in Data Warehouses.- A Parallel Implementation of the K Nearest Neighbours Classifier in Three Levels: Threads, MPI Processes and the Grid.- On the Use of the MMC Language to Utilize SIMD Instruction Set.- A Versatile Pipelined Hardware Implementation for Encryption and Decryption Using Advanced Encryption Standard.- 3: Numerical Methods.- Combinatorial Scientific Computing: The Enabling Power of Discrete Algorithms in Computational Science.- Improving the Numerical Simulation of an Airflow Problem with the BlockCGSI Algorithm.- EdgePack: A Parallel Vertex and Node Reordering Package for Optimizing Edge-Based Computations in Unstructured Grids.- Parallel Processing of Matrix Multiplication in a CPU and GPU Heterogeneous Environment.- Robust Two-Level Lower-Order Preconditioners for a Higher-Order Stokes Discretization with Highly Discontinuous Viscosities.- The Impact of Parallel Programming Models on the Performance of Iterative Linear Solvers for Finite Element Applications.- Efficient Parallel Algorithm for Constructing a Unit Triangular Matrix with Prescribed Singular Values.- A Rewriting System for the Vectorization of Signal Transforms.- High Order Fourier-Spectral Solutions to Self Adjoint Elliptic Equations.- Multiresolution Simulations Using Particles.- Evaluation of Several Variants of Explicitly Restarted Lanczos Eigensolvers and Their Parallel Implementations.- PyACTS: A High-Level Framework for Fast Development of High Performance Applications.- Sequential and Parallel Resolution of the Two-Group Transient Neutron Diffusion Equation Using Second-Degree Iterative Methods.- Enhancing the Performance of Multigrid Smoothers in Simultaneous Multithreading Architectures.- Block Iterative Algorithms for the Solution of Parabolic Optimal Control Problems.- Evaluation of Linear Solvers for Astrophysics Transfer Problems.- 4: Large Scale Simulations in Physics.- Scalable Cosmological Simulations on Parallel Machines.- Performance Evaluation of Scientific Applications on Modern Parallel Vector Systems.- Numerical Simulation of Three-Phase Flow in Heterogeneous Porous Media.- Simulation of Laser Propagation in a Plasma with a Frequency Wave Equation.- A Particle Gradient Evolutionary Algorithm Based on Statistical Mechanics and Convergence Analysis.- 5: Computing in Biosciences.- A Computational Framework for Cardiac Modeling Based on Distributed Computing and Web Applications.- Triangular Clique Based Multilevel Approaches to Identify Protein Functional Modules.- BioPortal: A Portal for Deployment of Bioinformatics Applications on Cluster and Grid Environments.- Workshop 1: Computational Grids and Clusters.- Adaptive Distributed Metamodeling.- Distributed General Logging Architecture for Grid Environments.- Interoperability Between UNICORE and ITBL.- Using Failure Injection Mechanisms to Experiment and Evaluate a Grid Failure Detector.- Semantic-Based Service Trading: Application to Linear Algebra.- Management of Services Based on a Semantic Description Within the GRID-TLSE Project.- Extending the Services and Sites of Production Grids by the Support of Advanced Portals.- Workshop 2: High-Performance Data Management in Grid Environments.- PSO-Grid Data Replication Service.- Execution Management of Scientific Models on Computational Grids.- Replica Refresh Strategies in a Database Cluster.- A Practical Evaluation of a Data Consistency Protocol for Efficient Visualization in Grid Applications.- Experiencing Data Grids.

Iterative solution of bem equations by GMRES algorithm

Abstract This paper presents a performance study of the GMRES algorithm for the solution of non-symmetric dense systems of equations arising from the boundary element discretization of two-dimensional elasticity. Comparisons with Gauss elimination and bi-conjugate gradients show the computer effectiveness and accuracy of the preconditioned GMRES algorithm.

Exploring many task computing in scientific workflows

One of the main advantages of using a scientific workflow management system (SWfMS) to orchestrate data flows among scientific activities is to control and register the whole workflow execution. The execution of activities within a workflow with high performance computing (HPC) presents challenges in SWfMS execution control. Current solutions leave the scheduling to the HPC queue system. Since the workflow execution engine does not run on remote clusters, SWfMS are not aware of the parallel strategy of the workflow execution. Consequently, remote execution control and provenance registry of the parallel activities is very limited from the SWfMS side. This work presents a set of components to be included on the workflow specification of any SWMfS to control parallelization of activities as MTC. In addition, these components can gather provenance data during remote workflow execution. Through these MTC components, the parallelization strategy can be registered and reused, and provenance data can be uniformly queried. We have evaluated our approach by performing parameter sweep parallelization in solving the incompressible 3D Navier-Stokes equations. Experimental results show the performance gains with the additional benefits of distributed provenance support.

Implicit SUPG solution of Euler equations using edge-based data structures

In this work we present an implicit, edge-based implementation of the semi-discrete SUPG formulation with shock-capturing for the Euler equations in conservative variables. By disassembling the resulting finite element matrices into their edge contributions, sparse matrix coefficients, residuals and matrix-vector products needed in Krylov-update techniques are computed based on edge data structures. The resulting solution method requires less memory and CPU time than element-based implementations.

Simple zero thickness kinematically consistent interface elements

Abstract Interface finite elements have been used in many geotechnical and engineering applications. Essentially, these elements must allow relative displacements between two bodies in contact, or separated by a thin material layer. Frequently, interface elements behave as linear elastic bodies up to a limiting stress state. This linear behavior of interfaces is very important, because it will establish when the slip and/or separation occurs, causing stress redistribution over the mesh. In this paper, the mechanical behavior of interface elements is discussed. It is shown that the kinematic inconsistency pointed by Kaliakin and Li [Comp. Geotech. 17 (1995) 225] for the element proposed by Goodman et al. [ASCE J. Soil Mech. Fdns. Div. 99 (1968) 637] also occurs for other interface models, and new interface elements for 2D and 3D analyses without kinematic inconsistencies are proposed.

Supporting dynamic parameter sweep in adaptive and user-steered workflow

Large-scale experiments in computational science are complex to manage. Due to its exploratory nature, several iterations evaluate a large space of parameter combinations. Scientists analyze partial results and dynamically interfere on the next steps of the simulation. Scientific workflow management systems can execute those experiments by providing process management, distributed execution and provenance data. However, supporting scientists in complex exploratory processes involving dynamic workflows is still a challenge. Features, such as user steering on workflows to track, evaluate and adapt the execution need to be designed to support iterative methods. We provide an approach to support dynamic parameter sweep, in which scientists can use the results obtained in a slice of the parameter space to improve the remainder of the execution. We propose new control structures to enable adaptive and user-steered workflows supporting iterative methods using dynamic mechanisms. We evaluate our approach using a proof of concept (Lanczos algorithm) workflow and the results show up to 78% of execution time saved.

Three-Dimensional Edge-Based SUPG Computation of Inviscid Compressible Flows With YZβ Shock-Capturing

The streamline-upwind/Petrov-Galerkin (SUPG) formulation of compressible flows based on conservation variables, supplemented with shock-capturing, has been successfully used over a quarter of a century. In this paper, for inviscid compressible flows, the YZβ shock-capturing parameter, which was developed recently and is based on conservation variables only, is compared with an earlier parameter derived based on the entropy variables. Our studies include comparing, in the context of these two versions of the SUPG formulation, computational efficiency of the element- and edge-based data structures in iterative computation of compressible flows. Tests include ID, 2D, and 3D examples.

A natural derivation of discontinuity capturing operator for convection–diffusion problems

Abstract The concept of effective transport velocity is introduced to derive a discontinuity capturing operator for convection–diffusion problems. The effective transport velocity , which depends both on the flow velocity and on the local solution gradient, is used to modify the classical representation of the convective term at the continuum level. As a result, a discontinuity capturing operator arises naturally in the derivation of Lax–Wendroff, Taylor–Galerkin and least-squares type approximations of the convection–diffusion equation. The numerical examples presented demonstrate the effectiveness of the proposed approach. These include the classical problem of the advection of a steep profile skew to the mesh and the computation of the temperature field in a free convection problem.

Miscible displacement simulation by finite element methods in distributed memory machines

Abstract Finite element methods taylored for large scale simulation of incompressible miscible displacement in porous media are presented. Employing same order Lagrangian interpolations for all variables, pressure is approximated by Galerkins method, global or local post-processing techniques are used to compute higher-order velocity approximations, and a stabilized Petrov—Galerkin formulation is applied to concentration equation. Error estimates are discussed as well as the parallel implementation on a distributed memory machine. Numerical simulations of tracer injection processes and miscible displacements with high adverse mobility ratios in two and three dimensions are reported.

Performance evaluation of block-diagonal preconditioners for the divergence-conforming B-Spline discretization of the Stokes system

Abstract The recently introduced divergence-conforming B-spline discretizations allow the construction of smooth discrete velocity–pressure pairs for viscous incompressible flows that are at the same time inf-sup stable and pointwise divergence-free. When applied to discretized Stokes equations, these spaces generate a symmetric and indefinite saddle-point linear system. Krylov subspace methods are usually the most efficient procedures to solve such systems. One of such methods, for symmetric systems, is the Minimum Residual Method (MINRES). However, the efficiency and robustness of Krylov subspace methods is closely tied to appropriate preconditioning strategies. For the discrete Stokes system, in particular, block-diagonal strategies provide efficient preconditioners. In this article, we compare the performance of block-diagonal preconditioners for several block choices. We verify how the eigenvalue clustering promoted by the preconditioning strategies affects MINRES convergence. We also compare the number of iterations and wall-clock timings. We conclude that among the building blocks we tested, the strategy with relaxed inner conjugate gradients preconditioned with incomplete Cholesky provided the best results.