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Second International Workshop on Software Engineering and Code Design in Parallel Meteorological and Oceanographic Applications

This report contains the abstracts and technical papers from the Second International Workshop on Software Engineering and Code Design in Parallel Meteorological and Oceanographic Applications, held June 15-18, 1998, in Scottsdale, Arizona. The purpose of the workshop is to bring together software developers in meteorology and oceanography to discuss software engineering and code design issues for parallel architectures, including Massively Parallel Processors (MPP's), Parallel Vector Processors (PVP's), Symmetric Multi-Processors (SMP's), Distributed Shared Memory (DSM) multi-processors, and clusters. Issues to be discussed include: (1) code architectures for current parallel models, including basic data structures, storage allocation, variable naming conventions, coding rules and styles, i/o and pre/post-processing of data; (2) designing modular code; (3) load balancing and domain decomposition; (4) techniques that exploit parallelism efficiently yet hide the machine-related details from the programmer; (5) tools for making the programmer more productive; and (6) the proliferation of programming models (F--, OpenMP, MPI, and HPF).

OKeefe, Matthew↗

Comparing the Performance of Two Dynamic Load Distribution Methods

Parallel processing of symbolic computations on a message-passing multi-processor presents one challenge: To effectively utilize the available processors, the load must be distributed uniformly to all the processors. However, the structure of these computations cannot be predicted in advance. go, static scheduling methods are not applicable. In this paper, we compare the performance of two dynamic, distributed load balancing methods with extensive simulation studies. The two schemes are: the Contracting Within a Neighborhood (CWN) scheme proposed by us, and the Gradient Model proposed by Lin and Keller. We conclude that although simpler, the CWN is significantly more effective at distributing the work than the Gradient model.

Kale, L. V.↗

Database Reorganization in Parallel Disk Arrays with I/O Service Stealing

We present a model for data reorganization in parallel disk systems that is geared towards load balancing in an environment with periodic access patterns. Data reorganization is performed by disk cooling, i.e. migrating files or extents from the hottest disks to the coldest ones. We develop an approximate queueing model for determining the effective arrival rates of cooling requests and discuss its use in assessing the costs versus benefits of cooling.

Zabback, Peter↗

A Robust and Scalable Software Library for Parallel Adaptive Refinement on Unstructured Meshes

The design and implementation of Pyramid, a software library for performing parallel adaptive mesh refinement (PAMR) on unstructured meshes, is described. This software library can be easily used in a variety of unstructured parallel computational applications, including parallel finite element, parallel finite volume, and parallel visualization applications using triangular or tetrahedral meshes. The library contains a suite of well-designed and efficiently implemented modules that perform operations in a typical PAMR process. Among these are mesh quality control during successive parallel adaptive refinement (typically guided by a local-error estimator), parallel load-balancing, and parallel mesh partitioning using the ParMeTiS partitioner. The Pyramid library is implemented in Fortran 90 with an interface to the Message-Passing Interface (MPI) library, supporting code efficiency, modularity, and portability. An EM waveguide filter application, adaptively refined using the Pyramid library, is illustrated.

Lou, John Z.↗

A Posteriori Error Estimation for Finite Volume and Finite Element Approximations Using Broken Space Approximation

We consider a posteriori error estimates for finite volume and finite element methods on arbitrary meshes subject to prescribed error functionals. Error estimates of this type are useful in a number of computational settings: (1) quantitative prediction of the numerical solution error, (2) adaptive meshing, and (3) load balancing of work on parallel computing architectures. Our analysis recasts the class of Godunov finite volumes schemes as a particular form of discontinuous Galerkin method utilizing broken space approximation obtained via reconstruction of cell-averaged data. In this general framework, weighted residual error bounds are readily obtained using duality arguments and Galerkin orthogonality. Additional consideration is given to issues such as nonlinearity, efficiency, and the relationship to other existing methods. Numerical examples are given throughout the talk to demonstrate the sharpness of the estimates and efficiency of the techniques. Additional information is contained in the original.

Barth, Timothy J.↗

Large-Scale Distributed Computational Fluid Dynamics on the Information Power Grid Using Globus

This paper describes an experiment in which a large-scale scientific application development for tightly-coupled parallel machines is adapted to the distributed execution environment of the Information Power Grid (IPG). A brief overview of the IPG and a description of the computational fluid dynamics (CFD) algorithm are given. The Globus metacomputing toolkit is used as the enabling device for the geographically-distributed computation. Modifications related to latency hiding and Load balancing were required for an efficient implementation of the CFD application in the IPG environment. Performance results on a pair of SGI Origin 2000 machines indicate that real scientific applications can be effectively implemented on the IPG; however, a significant amount of continued effort is required to make such an environment useful and accessible to scientists and engineers.

Barnard, Stephen↗

Visualization Co-Processing of a CFD Simulation

OVERFLOW, a widely used CFD simulation code, is combined with a visualization system, pV3, to experiment with an environment for simulation/visualization co-processing on a SGI Origin 2000 computer(O2K) system. The shared memory version of the solver is used with the O2K 'pfa' preprocessor invoked to automatically discover parallelism in the source code. No other explicit parallelism is enabled. In order to study the scaling and performance of the visualization co-processing system, sample runs are made with different processor groups in the range of 1 to 254 processors. The data exchange between the visualization system and the simulation system is rapid enough for user interactivity when the problem size is small. This shared memory version of OVERFLOW, with minimal parallelization, does not scale well to an increasing number of available processors. The visualization task takes about 18 to 30% of the total processing time and does not appear to be a major contributor to the poor scaling. Improper load balancing and inter-processor communication overhead are contributors to this poor performance. Work is in progress which is aimed at obtaining improved parallel performance of the solver and removing the limitations of serial data transfer to pV3 by examining various parallelization/communication strategies, including the use of the explicit message passing.

Vaziri, Arsi↗

Avoiding Braess' Paradox Through Collective Intelligence

In an Ideal Shortest Path Algorithm (ISPA), at each moment each router in a network sends all of its traffic down the path that will incur the lowest cost to that traffic. In the limit of an infinitesimally small amount of traffic for a particular router, its routing that traffic via an ISPA is optimal, as far as cost incurred by that traffic is concerned. We demonstrate though that in many cases, due to the side-effects of one router's actions on another routers performance, having routers use ISPA's is suboptimal as far as global aggregate cost is concerned, even when only used to route infinitesimally small amounts of traffic. As a particular example of this we present an instance of Braess' paradox for ISPA'S, in which adding new links to a network decreases overall throughput. We also demonstrate that load-balancing, in which the routing decisions are made to optimize the global cost incurred by all traffic currently being routed, is suboptimal as far as global cost averaged across time is concerned. This is also due to "side-effects", in this case of current routing decision on future traffic. The theory of COllective INtelligence (COIN) is concerned precisely with the issue of avoiding such deleterious side-effects. We present key concepts from that theory and use them to derive an idealized algorithm whose performance is better than that of the ISPA, even in the infinitesimal limit. We present experiments verifying this, and also showing that a machine-learning-based version of this COIN algorithm in which costs are only imprecisely estimated (a version potentially applicable in the real world) also outperforms the ISPA, despite having access to less information than does the ISPA. In particular, this COIN algorithm avoids Braess' paradox.

Wolpert , David H.↗

A Framework for WWW Query Processing

Query processing is the most common operation in a DBMS. Sophisticated query processing has been mainly targeted at a single enterprise environment providing centralized control over data and metadata. Submitting queries by anonymous users on the web is different in such a way that load balancing or DBMS' accessing control becomes the key issue. This paper provides a solution by introducing a framework for WWW query processing. The success of this framework lies in the utilization of query optimization techniques and the ontological approach. This methodology has proved to be cost effective at the NASA Goddard Space Flight Center Distributed Active Archive Center (GDAAC).

Wu, Binghui Helen↗

Cluster Computation of Flight Reynolds Number Flows

The performance of a workstation cluster used for the solution of the Reynolds-averaged Navier-Stokes equations is compared with a conventional vector supercomputer architecture. The application simulation of the steady flowfield about a transonic transport was computed using an implicit diagonal scheme in an overset mesh framework. Static load balancing was used, while coarse grain decomposition was achieved by solution of a grid zone per processor. Price/performance ratios are estimated for several scenarios in which such clusters may be utilized.

Atwood, Christopher A.↗

Parallel and Distributed Computational Fluid Dynamics: Experimental Results and Challenges

This paper describes several results of parallel and distributed computing using a large scale production flow solver program. A coarse grained parallelization based on clustering of discretization grids combined with partitioning of large grids for load balancing is presented. An assessment is given of its performance on distributed and distributed-shared memory platforms using large scale scientific problems. An experiment with this solver, adapted to a Wide Area Network execution environment is presented. We also give a comparative performance assessment of computation and communication times on both the tightly and loosely-coupled machines.

Djomehri, Mohammad Jahed↗

Parallel Programming Strategies for Irregular Adaptive Applications

Achieving scalable performance for dynamic irregular applications is eminently challenging. Traditional message-passing approaches have been making steady progress towards this goal; however, they suffer from complex implementation requirements. The use of a global address space greatly simplifies the programming task, but can degrade the performance for such computations. In this work, we examine two typical irregular adaptive applications, Dynamic Remeshing and N-Body, under competing programming methodologies and across various parallel architectures. The Dynamic Remeshing application simulates flow over an airfoil, and refines localized regions of the underlying unstructured mesh. The N-Body experiment models two neighboring Plummer galaxies that are about to undergo a merger. Both problems demonstrate dramatic changes in processor workloads and interprocessor communication with time; thus, dynamic load balancing is a required component.

Biswas, Rupak↗

Platform-Independence and Scheduling In a Multi-Threaded Real-Time Simulation

Aviation research often relies on real-time, pilot-in-the-loop flight simulation as a means to develop new flight software, flight hardware, or pilot procedures. Often these simulations become so complex that a single processor is incapable of performing the necessary computations within a fixed time-step. Threads are an elegant means to distribute the computational work-load when running on a symmetric multi-processor machine. However, programming with threads often requires operating system specific calls that reduce code portability and maintainability. While a multi-threaded simulation allows a significant increase in the simulation complexity, it also increases the workload of a simulation operator by requiring that the operator determine which models run on which thread. To address these concerns an object-oriented design was implemented in the NASA Langley Standard Real-Time Simulation in C++ (LaSRS++) application framework. The design provides a portable and maintainable means to use threads and also provides a mechanism to automatically load balance the simulation models.

Sugden, Paul P.↗

Navier-Stokes Aerodynamic Simulation of the V-22 Osprey on the Intel Paragon MPP

The paper will describe the Development of a general three-dimensional multiple grid zone Navier-Stokes flowfield simulation program (ENS3D-MPP) designed for efficient execution on the Intel Paragon Massively Parallel Processor (MPP) supercomputer, and the subsequent application of this method to the prediction of the viscous flowfield about the V-22 Osprey tiltrotor vehicle. The flowfield simulation code solves the thin Layer or full Navier-Stoke's equation - for viscous flow modeling, or the Euler equations for inviscid flow modeling on a structured multi-zone mesh. In the present paper only viscous simulations will be shown. The governing difference equations are solved using a time marching implicit approximate factorization method with either TVD upwind or central differencing used for the convective terms and central differencing used for the viscous diffusion terms. Steady state or Lime accurate solutions can be calculated. The present paper will focus on steady state applications, although time accurate solution analysis is the ultimate goal of this effort. Laminar viscosity is calculated using Sutherland's law and the Baldwin-Lomax two layer algebraic turbulence model is used to compute the eddy viscosity. The Simulation method uses an arbitrary block, curvilinear grid topology. An automatic grid adaption scheme is incorporated which concentrates grid points in high density gradient regions. A variety of user-specified boundary conditions are available. This paper will present the application of the scalable and superscalable versions to the steady state viscous flow analysis of the V-22 Osprey using a multiple zone global mesh. The mesh consists of a series of sheared cartesian grid blocks with polar grids embedded within to better simulate the wing tip mounted nacelle. MPP solutions will be shown in comparison to equivalent Cray C-90 results and also in comparison to experimental data. Discussions on meshing considerations, wall clock execution time, load balancing, and scalability will be provided.

Vadyak, Joseph↗

A Unique Power System For The ISS Fluids And Combustion Facility

Unique power control technology has been incorporated into an electrical power control unit (EPCU) for the Fluids and Combustion Facility (FCF). The objective is to maximize science throughput by providing a flexible power system that is easily reconfigured by the science payload. Electrical power is at a premium on the International Space Station (ISS). The EPCU utilizes advanced power management techniques to maximize the power available to the FCF experiments. The EPCU architecture enables dynamic allocation of power from two ISS power channels for experiments. Because of the unique flexible remote power controller (FRPC) design, power channels can be paralleled while maintaining balanced load sharing between the channels. With an integrated and redundant architecture, the EPCU can tolerate multiple faults and still maintain FCF operation. It is important to take full advantage of the EPCU functionality. The EPCU acts as a buffer between the experimenter and the ISS power system with all its complex requirements. However, FCF science payload developers will still need to follow guidelines when designing the FCF payload power system. This is necessary to ensure power system stability, fault coordination, electromagnetic compatibility, and maximum use of available power for gathering scientific data.

Fox, David A.↗

RANS-MP: A Portable Parallel Navier-Stokes Solver

RANS-MP, a new implementation of a single-grid Navier-Stokes solver using the diagonalized Beam-Warming approximate-factorization scheme, is presented. This first release of the completely rewritten solver employs the following optimizations: (1) Bi-directional multi-partition method for the ADI solver part; this improves granularity and load balance; (2) Improved cache usage through elimination of non-unit-stride array access (possible in part due to multi-partitioning); (3) Preprocessing of communicating boundary conditions to streamline logic during time stepping; (4) Truly parallel, high-performance I/O using the newly-developed MPI-IO library; (5) Elimination of large amounts of redundant operations through efficient use of workspace. Results of some realistic wing computations on the IBM SP2 computer will be presented. We will demonstrate that excellent absolute performance and scalability are obtained with RANS-MP, even for relatively small grid sizes. Besides high performance, an outstanding feature of RANS-MP is its true portability, due to the use of the portable message passing and I/O libraries MPI and MPI-IO.

VanderWijngaart, Rob F.↗

A Portable MPI Implementation of the SPAI Preconditioner in ISIS++

A parallel MPI implementation of the Sparse Approximate Inverse (SPAI) preconditioner is described. SPAI has proven to be a highly effective preconditioner, and is inherently parallel because it computes columns (or rows) of the preconditioning matrix independently. However, there are several problems that must be addressed for an efficient MPI implementation: load balance, latency hiding, and the need for one-sided communication. The effectiveness, efficiency, and scaling behavior of our implementation will be shown for different platforms.

Barnard, Stephen T.↗

A Fast-Time Study of Aircraft Reordering in Arrival Sequencing and Scheduling

In order to ensure that the safe capacity of the terminal area is not exceeded, Air Traffic Management ATM often places restrictions on arriving flights transitioning from en route airspace to terminal airspace. This restriction of arrival traffic is commonly referred to as arrival flow management, and includes techniques such as metering, vectoring, fix-load balancing, and the imposition of miles-in-trail separations. These restrictions are enacted without regard for the relative priority which airlines may be placing on individual flights based on factors such as crew criticality, passenger connectivity, critical turn times, gate availability, on-time performance, fuel status, or runway preference. The development of new arrival flow management techniques which take into consideration priorities expressed by air carriers will likely reduce the economic impact of ATM restrictions on the airlines and lead to increased airline economic efficiency by allowing airlines to have greater control over their individual arrival banks of aircraft. NASA and the Federal Aviation Administration (FAA) have designed and developed a suite of software decision support tools (DSTs) collectively known as the Center TRACON Automation System (CTAS). One of these tools, the Traffic Management Advisor (TMA) is currently being used at the Fort Worth Air Route Traffic Control Center to perform arrival flow management of traffic into the Dallas/Fort Worth airport (DFW). The TMA is a time-based strategic planning tool that assists Traffic Management Coordinators (TMCs) and En Route Air Traffic Controllers in efficiently balancing arrival demand with airport capacity. The primary algorithm in the TMA is a real-time scheduler which generates efficient landing sequences and landing times for arrivals within about 200 no a. from touchdown. This scheduler will sequence aircraft so that they arrive in a first- come - first-served (FCFS) order. While FCFS sequencing establishes a fair order based on estimated times of arrival, it does not take into account individual airline priorities among incoming flights. NASA is exploring the possibility of allowing airlines to express relative arrival priorities to air traffic management through the development of new CTAS scheduling algorithms which take into consideration airline arrival preferences. The accommodation of airline priorities in arrival sequencing and scheduling would under most circumstances result in a deviation from a "natural" or FCFS arrival order. As a First step toward developing airline influenced sequencing algorithms, an investigation was conducted to determine the feasibility of reordering arrival traffic from a strict FCFS sequence. A fast-time simulation has been developed which allows statistical evaluation of sequencing and scheduling algorithms for arrival traffic at the Dallas/Fort Worth Airport. In contrast to real-time simulation or field tests, which would require on the order of ninety minutes to examine a single traffic rush period, the fast-time simulation allows examination of multiple rush periods in a matter of seconds.

Carr, Greg↗