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Parallel Computing Strategies for Irregular Algorithms

Parallel computing promises several orders of magnitude increase in our ability to solve realistic computationally-intensive problems, but relies on their efficient mapping and execution on large-scale multiprocessor architectures. Unfortunately, many important applications are irregular and dynamic in nature, making their effective parallel implementation a daunting task. Moreover, with the proliferation of parallel architectures and programming paradigms, the typical scientist is faced with a plethora of questions that must be answered in order to obtain an acceptable parallel implementation of the solution algorithm. In this paper, we consider three representative irregular applications: unstructured remeshing, sparse matrix computations, and N-body problems, and parallelize them using various popular programming paradigms on a wide spectrum of computer platforms ranging from state-of-the-art supercomputers to PC clusters. We present the underlying problems, the solution algorithms, and the parallel implementation strategies. Smart load-balancing, partitioning, and ordering techniques are used to enhance parallel performance. Overall results demonstrate the complexity of efficiently parallelizing irregular algorithms.

Biswas, Rupak↗

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.↗

Dynamic Harris current sheet thickness from Cluster current density and plasma measurements

We use the first accurate measurements of current densities in the plasma sheet to calculate the half-thickness and position of the current sheet as a function of time. Our technique assumes a Harris current sheet model, which is parameterized by lobe magnetic field B(o), current sheet half-thickness h, and current sheet position z(sub o). Cluster measurements of magnetic field, current density, and plasma pressure are used to infer the three parameters as a function of time. We find that most long timescale (6-12 hours) current sheet crossings observed by Cluster cannot be described by a static Harris current sheet with a single set of parameters B(sub o), h, and z(sub o). Noting the presence of high-frequency fluctuations that appear to be superimposed on lower frequency variations, we average over running 6-min intervals and use the smoothed data to infer the parameters h(t) and z(sub o)(t), constrained by the pressure balance lobe magnetic field B(sub o)(t). Whereas this approach has been used in previous studies, the spatial gnuhen& now provided by the Cluster magnetometers were unavailable or not well constrained in earlier studies. We place the calculated hdf&cknessa in a magnetospheric context by examining the change in thickness with substorm phase for three case study events and 21 events in a superposed epoch analysis. We find that the inferred half-thickness in many cases reflects the nominal changes experienced by the plasma sheet during substorms (i.e., thinning during growth phase, thickening following substorm onset). We conclude with an analysis of the relative contribution of (Delta)B(sub z)/(Delta)X to the cross-tail current density during substorms. We find that (Delta)B(sub z)/(Delta)X can contribute a significant portion of the cross-tail c m n t around substorm onset.

Thompson, S. M.↗

A Multi-Level Parallelization Concept for High-Fidelity Multi-Block Solvers

The integration of high-fidelity Computational Fluid Dynamics (CFD) analysis tools with the industrial design process benefits greatly from the robust implementations that are transportable across a wide range of computer architectures. In the present work, a hybrid domain-decomposition and parallelization concept was developed and implemented into the widely-used NASA multi-block Computational Fluid Dynamics (CFD) packages implemented in ENSAERO and OVERFLOW. The new parallel solver concept, PENS (Parallel Euler Navier-Stokes Solver), employs both fine and coarse granularity in data partitioning as well as data coalescing to obtain the desired load-balance characteristics on the available computer platforms. This multi-level parallelism implementation itself introduces no changes to the numerical results, hence the original fidelity of the packages are identically preserved. The present implementation uses the Message Passing Interface (MPI) library for interprocessor message passing and memory accessing. By choosing an appropriate combination of the available partitioning and coalescing capabilities only during the execution stage, the PENS solver becomes adaptable to different computer architectures from shared-memory to distributed-memory platforms with varying degrees of parallelism. The PENS implementation on the IBM SP2 distributed memory environment at the NASA Ames Research Center obtains 85 percent scalable parallel performance using fine-grain partitioning of single-block CFD domains using up to 128 wide computational nodes. Multi-block CFD simulations of complete aircraft simulations achieve 75 percent perfect load-balanced executions using data coalescing and the two levels of parallelism. SGI PowerChallenge, SGI Origin 2000, and a cluster of workstations are the other platforms where the robustness of the implementation is tested. The performance behavior on the other computer platforms with a variety of realistic problems will be included as this on-going study progresses.

Hatay, Ferhat F.↗

Using the GeoFEST Faulted Region Simulation System

GeoFEST (the Geophysical Finite Element Simulation Tool) simulates stress evolution, fault slip and plastic/elastic processes in realistic materials, and so is suitable for earthquake cycle studies in regions such as Southern California. Many new capabilities and means of access for GeoFEST are now supported. New abilities include MPI-based cluster parallel computing using automatic PYRAMID/Parmetis-based mesh partitioning, automatic mesh generation for layered media with rectangular faults, and results visualization that is integrated with remote sensing data. The parallel GeoFEST application has been successfully run on over a half-dozen computers, including Intel Xeon clusters, Itanium II and Altix machines, and the Apple G5 cluster. It is not separately optimized for different machines, but relies on good domain partitioning for load-balance and low communication, and careful writing of the parallel diagonally preconditioned conjugate gradient solver to keep communication overhead low. Demonstrated thousand-step solutions for over a million finite elements on 64 processors require under three hours, and scaling tests show high efficiency when using more than (order of) 4000 elements per processor. The source code and documentation for GeoFEST is available at no cost from Open Channel Foundation. In addition GeoFEST may be used through a browser-based portal environment available to approved users. That environment includes semi-automated geometry creation and mesh generation tools, GeoFEST, and RIVA-based visualization tools that include the ability to generate a flyover animation showing deformations and topography. Work is in progress to support simulation of a region with several faults using 16 million elements, using a strain energy metric to adapt the mesh to faithfully represent the solution in a region of widely varying strain.

Geophyical Finite Element Simulation Tool (GeoFEST↗

Dynamic Load-Balancing for Distributed Heterogeneous Computing of Parallel CFD Problems

The developed methodology is aimed at improving the efficiency of executing block-structured algorithms on parallel, distributed, heterogeneous computers. The basic approach of these algorithms is to divide the flow domain into many sub- domains called blocks, and solve the governing equations over these blocks. Dynamic load balancing problem is defined as the efficient distribution of the blocks among the available processors over a period of several hours of computations. In environments with computers of different architecture, operating systems, CPU speed, memory size, load, and network speed, balancing the loads and managing the communication between processors becomes crucial. Load balancing software tools for mutually dependent parallel processes have been created to efficiently utilize an advanced computation environment and algorithms. These tools are dynamic in nature because of the chances in the computer environment during execution time. More recently, these tools were extended to a second operating system: NT. In this paper, the problems associated with this application will be discussed. Also, the developed algorithms were combined with the load sharing capability of LSF to efficiently utilize workstation clusters for parallel computing. Finally, results will be presented on running a NASA based code ADPAC to demonstrate the developed tools for dynamic load balancing.

Ecer, A.↗

Balanced-Load Real-Time Multiprocessor System

Modularity and parallelism provide tolerance to faults and high throughput capacity. System, called MAX, is network of interconnected computers. MAX cluster consists of group of modules - each semiautonomous computer. Modules connected to each other and to other clusters by global bus and circuit-switched communication mesh.

Rasmussen, Robert D.↗

Multiband observations of Cygnus A: A study of pressure balance in the core of a powerful radio galaxy

Cygnus A is a powerful double radio source associated with a giant elliptical galaxy at the center of a poor cluster of galaxies. The radio source also sits within the core radius of a dense, cooling flow, x ray emitting cluster gas. Optical spectroscopy and narrow band imaging have revealed copious amounts of narrow line emission from the inner 20 kpc of the associated galaxy. Researchers assume H sub o = 75 km sec (-1) Mpc(-1). Discussed here are the pressures in the three components of the Interstellar Medium (ISM) (i.e., the radio, x ray, and line emitting fluids) within a radius of about 15 kpc of the active nucleus of the Cygnus A galaxy.

Carilli, Chris↗

Confinement of radio galaxies in rich clusters

X-ray observations obtained with the Einstein Observatory are presented for the Abell clusters A 98, A 160, A 278, and A 569, which are characterized by the presence of an extended radio source associated with the brightest cluster galaxy. The X-ray brightness profiles are fitted with a hydrostatic-thermal model to determine the physical parameters of the X-ray emitting gas and the behavior of the thermal pressure in each cluster. The gas thermal pressure is then compared with the nonthermal pressure within the radio sources, and the conditions for pressure balance are analyzed. The radio source components show a minimum pressure lower than the pressure of the ambient gas. Balance between internal and external pressure is obtained in the case that the usual assumptions for the computation of the energy density in the radio source components are not valid (Phi less than 1, k greater than 1) or that physical conditions are out of equipartition.

Feretti, L.↗

Computational strategies for three-dimensional flow simulations on distributed computer systems

This research effort is directed towards an examination of issues involved in porting large computational fluid dynamics codes in use within the industry to a distributed computing environment. This effort addresses strategies for implementing the distributed computing in a device independent fashion and load balancing. A flow solver called TEAM presently in use at Lockheed Aeronautical Systems Company was acquired to start this effort. The following tasks were completed: (1) The TEAM code was ported to a number of distributed computing platforms including a cluster of HP workstations located in the School of Aerospace Engineering at Georgia Tech; a cluster of DEC Alpha Workstations in the Graphics visualization lab located at Georgia Tech; a cluster of SGI workstations located at NASA Ames Research Center; and an IBM SP-2 system located at NASA ARC. (2) A number of communication strategies were implemented. Specifically, the manager-worker strategy and the worker-worker strategy were tested. (3) A variety of load balancing strategies were investigated. Specifically, the static load balancing, task queue balancing and the Crutchfield algorithm were coded and evaluated. (4) The classical explicit Runge-Kutta scheme in the TEAM solver was replaced with an LU implicit scheme. And (5) the implicit TEAM-PVM solver was extensively validated through studies of unsteady transonic flow over an F-5 wing, undergoing combined bending and torsional motion. These investigations are documented in extensive detail in the dissertation, 'Computational Strategies for Three-Dimensional Flow Simulations on Distributed Computing Systems', enclosed as an appendix.

Sankar, Lakshmi N.↗

A Study of Parallel Scalability and Dynamic Workload Balancing in GlennICE

The Glenn Icing Computational Environment (GlennICE) is a computational tool designed to calculate ice growth on complex three-dimensional geometries. It utilizes user-supplied computational fluid dynamics solutions for the geometry of interest. Key developments include advancements in convergence of collection efficiency, trajectory optimization, and refinement methodology. These improvements have significantly enhanced GlennICE’s efficiency for practical engineering applications. A recent study focused on benchmarking GlennICE’s scalability in a parallel environment using static scheduling. Findings indicated a potential twofold increase in efficiency through workload balance enhancements. This paper presents an analysis of the solver’s new workload balancing improvements, incorporating shared memory and dynamic scheduling routines. Results demonstrate a highly efficient and consistent algorithm across high-performance computing clusters.

Computational Icing↗

A Study of Parallel Scalability and Dynamic Workload Balancing in GlennICE

The Glenn Icing Computational Environment (GlennICE) is a computational tool designed to calculate ice growth on complex three-dimensional geometries. It utilizes user-supplied computational fluid dynamics solutions for the geometry of interest. Key developments include advancements in convergence of collection efficiency, trajectory optimization, and refinement methodology. These improvements have significantly enhanced GlennICE’s efficiency for practical engineering applications. A recent study focused on benchmarking GlennICE’s scalability in a parallel environment using static scheduling. Findings indicated a potential twofold increase in efficiency through workload balance enhancements. This paper presents an analysis of the solver’s new workload balancing improvements, incorporating shared memory and dynamic scheduling routines. Results demonstrate a highly efficient and consistent algorithm across high-performance computing clusters.

Computational Icing↗

Traction Drives for Zero Stick-Slip Robots, and Reaction Free, Momentum Balanced Systems

Two differential (dual input, single output) drives (a roller-gear and a pure roller), and a momentum balanced (single input, dual output) drive (pure roller ) were designed, fabricated, and tested. The differential drives are each rated at 295 rad/sec (2800 rpm) input speed, 450 N-m (4,000 in-lbf) output torque. The momentum balanced drive is rated at 302 rad/sec (2880 rpm) input speed, and dual output torques of 434N-m (3840 in-lbf). The Dual Input Differential Roller-Gear Drive (DC-700) has a planetary roller-gear system with a reduction ratio (one input driving the output with the second input fixed) of 29.23: 1. The Dual Input Differential Roller Drive (DC-500) has a planetary roller system with a reduction ratio of approximately 24:1. Each of the differential drives features dual roller-gear or roller arrangements consisting of a sun, four first row planets, four second row planets, and a ring. The Momentum Balanced (Grounded Ring) Drive (DC-400) has a planetary roller system with a reduction ratio of 24:1 with both outputs counterrotating at equal speed. Its single roller cluster consists of a sun, five first and five second row planets, a roller cage or spider and a ring. Outputs are taken from both the roller cage and the ring which counterrotate. Test results reported for all three drives include angular and torque ripple (linearity and cogging), viscous and Coulomb friction, and forward and reverse power efficiency. Of the two differential drives, the Differential Roller Drive had better linearity and less cogging than did the Differential Roller-Gear Drive, but it had higher friction and lower efficiency (particularly at low power throughput levels). Use of full preloading rather than a variable preload system in the Differential Roller Drive assessed a heavy penalty in part load efficiency. Maximum measured efficiency (ratio of power out to power in) was 95% for the Differential Roller-Gear Drive and 86% for the Differential Roller Drive. The Momentum Balanced (Grounded Ring) Drive performed as expected kinematically. Reduction r-atios to the two counterrotating outputs (design nominal=24:1) were measured to be 23.98:1 and 24.12:1 at zero load.. At 25ONm (2200 in-lbf) output torque the ratio changed 2% due to roller creep. This drive was the smoothest of all three as determined from linearity and cogging tests, and maximum measured efficiency (ratio of power out to power in) was 95%. The disadvantages of full preloading as comvared to variable preload were apparent in this drive as in the Differential Roller Drive. Efficiencies at part load were low, but improved dramatically with increases in torque. These were consistent with friction measurements which indicated losses primarily from Coulomb friction. The initial preload level setting was low so roller slip was encountered at higher torques during testing.

Anderson, William J.↗

Electra: A Modular-Based Expansion of NASA's Supercomputing Capability

NASA has increasingly relied on high-performance computing (HPC) re- sources for computational modeling, simulation, and data analysis to meet the science and engineering goals of its missions in space exploration, aeronautics, and Earth and space science. The NASA Advanced Supercomputing (NAS) Division at Ames Research Center in Silicon Valley, Calif., hosts NASA’s premier supercomputing resources, integral to achieving and enhancing the success of the agency’s missions. NAS provides a balanced environment, funded under the High-End Computing Capability (HECC) project, comprised of world-class supercomputers, including its flagship distributed-memory cluster, Pleiades; high-speed networking; and massive data storage facilities, along with multi-disciplinary support teams for user support, code porting and optimization, and large-scale data analysis and scientific visualization. However, as scientists have increased the fidelity of their simulations and engineers are conducting larger parameter-space studies, the requirements for supercomputing resources have been growing by leaps and bounds. With the facility housing the HECC systems reaching its power and cooling capacity, NAS undertook a prototype project to investigate an alternative approach for housing supercomputers. Modular supercomputing, or container-based computing, is an innovative concept for expanding NASA’s HPC capabilities. With modular supercomputing, additional containers—similar to portable storage pods—can be connected together as needed to accommodate the agency’s ever-increasing demand for computing resources. In addition, taking advantage of the local weather permits the use of cooling technologies that would additionally save energy and reduce annual water usage. The first stage of NASA’s Modular Supercomputing Facility (MSF) prototype, which resulted in a 1,000 square-foot module on a concrete pad with room for 16 compute racks, was completed in Fall 2016 and an SGI (now HPE) computer system, named Electra, was deployed there in early 2017. Cooling is performed via an evaporative system built into the module, and preliminary experience shows a Power Usage Effectiveness (PUE) measurement of 1.03. Electra achieved over a petaflop on the LINPACK benchmark, sufficient to rank number 96 on the November 2016 TOP500 list [14]. The system consists of 1,152 InfiniBand-connected Intel Xeon Broadwell-based nodes. Its users access their files on a facility-wide file system shared by all HECC compute assets via Mellanox MetroX InfiniBand extenders, which connect the Electra fabric to Lustre routers in the primary facility over fiber-optic links about 900 feet long. The MSF prototype has exceeded expectations and is serving as a blueprint for future expansions. In the remainder of this chapter, we detail how modular data center technology can be used to expand an existing compute resource. We begin by describing NASA’s requirements for supercomputing and how resources were provided prior to the integration of the Electra module-based system.

Biswas, Rupak↗

Properties of African squall lines inferred from time-lapse satellite imagery

Analysis of 48 h of time-lapse satellite imagery of a family of squall lines in Africa links the phenomena with a characteristic cloud cluster and with a wind field perturbation which is enhanced in passing through an African easterly wave trough. A thin 'arc line' of low-level developing cumulus, a salient feature of the squall lines on the imagery, is shown to occur at the front boundary of the mesoscale/convective scale subsidence. Analysis of the wind field indicates that a squall line is associated with a vorticity center in the mid-level easterly flow which accompanies the mesoscale subsidence which, in turn, contributes to further forced ascent of subcloud air along the front of the squall line into convective towers which merge into an extensive anvil. The squall lines evolved through a life cycle of 6 to 12 h while the larger cloud cluster and wind perturbation lasted over 48 h. The magnitude of the vertical mass exchange suggests that squall-line families contribute significantly to the tropical energy balance.

Fortune, M.↗

Predicting Cost/Performance Trade-Offs for Whitney: A Commodity Computing Cluster

Recent advances in low-end processor and network technology have made it possible to build a "supercomputer" out of commodity components. We develop simple models of the NAS Parallel Benchmarks version 2 (NPB 2) to explore the cost/performance trade-offs involved in building a balanced parallel computer supporting a scientific workload. We develop closed form expressions detailing the number and size of messages sent by each benchmark. Coupling these with measured single processor performance, network latency, and network bandwidth, our models predict benchmark performance to within 30%. A comparison based on total system cost reveals that current commodity technology (200 MHz Pentium Pros with 100baseT Ethernet) is well balanced for the NPBs up to a total system cost of around $1,000,000.

Becker, Jeffrey C.↗

Predicting Cost/Performance Trade-offs For Whitney: A Commodity Computing Cluster

Recent advances in low-end processor and network technology have made it possible to build a "supercomputer" out of commodity components. We develop simple models of the NAS Parallel Benchmarks version 2 (NPB 2) to explore the cost/performance trade-offs involved in building a balanced parallel computer supporting a scientific workload. By measuring single processor benchmark performance, network latency, and network bandwidth, and using closed form expressions detailing the number and size of messages sent by each benchmark, our models predict benchmark performance to within 30%. A comparison based on total system cost reveals that current commodity technology (200 MHz Pentium Pros with 100baseT Ethernet) is well balanced for the NPBs up to a total system cost of around $ 1,000,000.

Becker, Jeffrey C.↗

Operational Dynamic Configuration Analysis

Sectors may combine or split within areas of specialization in response to changing traffic patterns. This method of managing capacity and controller workload could be made more flexible by dynamically modifying sector boundaries. Much work has been done on methods for dynamically creating new sector boundaries [1-5]. Many assessments of dynamic configuration methods assume the current day baseline configuration remains fixed [6-7]. A challenging question is how to select a dynamic configuration baseline to assess potential benefits of proposed dynamic configuration concepts. Bloem used operational sector reconfigurations as a baseline [8]. The main difficulty is that operational reconfiguration data is noisy. Reconfigurations often occur frequently to accommodate staff training or breaks, or to complete a more complicated reconfiguration through a rapid sequence of simpler reconfigurations. Gupta quantified a few aspects of airspace boundary changes from this data [9]. Most of these metrics are unique to sector combining operations and not applicable to more flexible dynamic configuration concepts. To better understand what sort of reconfigurations are acceptable or beneficial, more configuration change metrics should be developed and their distribution in current practice should be computed. This paper proposes a method to select a simple sequence of configurations among operational configurations to serve as a dynamic configuration baseline for future dynamic configuration concept assessments. New configuration change metrics are applied to the operational data to establish current day thresholds for these metrics. These thresholds are then corroborated, refined, or dismissed based on airspace practitioner feedback. The dynamic configuration baseline selection method uses a k-means clustering algorithm to select the sequence of configurations and trigger times from a given day of operational sector combination data. The clustering algorithm selects a simplified schedule containing k configurations based on stability score of the sector combinations among the raw operational configurations. In addition, the number of the selected configurations is determined based on balance between accuracy and assessment complexity.

Lai, Chok Fung↗