State of the Art in Parallel Computing with R

R is a mature open-source programming language for statistical computing and graphics. Many areas of statistical research are experiencing rapid growth in the size of data sets. Methodological advances drive increased use of simulations. A common approach is to use parallel computing. This paper presents an overview of techniques for parallel computing with R on computer clusters, on multi-core systems, and in grid computing. It reviews sixteen different packages, comparing them on their state of development, the parallel technology used, as well as on usability, acceptance, and performance. Two packages (snow, Rmpi) stand out as particularly suited to general use on computer clusters. Packages for grid computing are still in development, with only one package currently available to the end user. For multi-core systems five different packages exist, but a number of issues pose challenges to early adopters. The paper concludes with ideas for further developments in high performance computing with R. Example code is available in the appendix.

An empirical evaluation of techniques for parallel simulation of message passing networks

209 p.[EN]In the field of computer design, simulation is an essential tool to validate and evaluate architectural proposals. Conventional simulation techniques, designed for their use in sequential computers, are too slow if the system to simulate is large or complex. The aim of this work is to search for techniques to accelerate simulations exploiting the parallelism available in current, commercial multicomputers, and to use these techniques to study a model of a message router. This router has been designed to constitute the communication infrastructure of a (hypothetical) massively parallel computer. Three parallel simulation techniques have been considered: synchronous, asynchronous-conservative and asynchronous-optimistic. These algorithms have been implemented in three multicomputers: a transputer-based Supernode, an Intel Paragon and a network of workstations. The influence that factors such as the characteristics of the simulated models, the organization of the simulators and the characteristics of the target multicomputers have in the performance of the simulations has been measured and characterized. It is concluded that optimistic parallel simulation techniques are not suitable for the considered kind of models, although they may provide good performance in other environments. A network of workstations is not the right platform for our experiments, because the communication demands of the parallel simulators surpass the abilities of local area networks—the granularity is too fine. Synchronous and conservative parallel simulation techniques perform very well in the Supernode and in the Paragon, specially if the model to simulate is complex or large—precisely the worst case for traditional, sequential simulators. This way, studies previously considered as unrealizable, due to their exceedingly high computational cost, can be performed in reasonable times. Additionally, the spectrum of possibilities of using multicomputers can be broadened to execute more than numeric applications.[ES]En el ámbito del diseño de computadores, la simulación es una herramienta imprescindible para la validación y evaluación de cualquier propuesta arquitectónica. Las ténicas convencionales de simulación, diseñadas para su utilización en computadores secuenciales, son demasiado lentas si el sistema a simular es grande o complejo. El objetivo de esta tesis es buscar técnicas para acelerar estas simulaciones, aprovechando el paralelismo disponible en multicomputadores comerciales, y usar esas técnicas para el estudio de un modelo de encaminador de mensajes. Este encaminador está diseñado para formar infraestructura de comunicaciones de un hipotético computador masivamente paralelo. En este trabajo se consideran tres técnicas de simulación paralela: síncrona, asíncrona-conservadora y asíncrona-optimista. Estos algoritmos se han implementado en tres multicomputadores: un Supernode basado en Transputers, un Intel Paragon y una red de estaciones de trabajo. Se caracteriza la influencia que tienen en las prestaciones de los simuladores aspectos tales como los parámetros del modelo simulado, la organización del simulador y las características del multicomputador utilizado. Se concluye que las técnicas de simulación paralela optimista no resultan adecuadas para trabajar con el modelo considerado, aunque pueden ofrecer un buen rendimiento en otros entornos. La red de estaciones de trabajo no resulta una plataforma apropiada para estas simulaciones, ya que una red local no reúne condiciones para la ejecución de aplicaciones paralelas de grano fino. Las técnicas de simulación paralela síncrona y conservadora dan muy buenos resultados en el Supernode y en el Paragon, especialmente si el modelo a simular es complejo o grande—precisamente el peor caso para los algoritmos secuenciales. De esta forma, estudios previamente considerados inviables, por ser demasiado costosos computacionalmente, pueden realizarse en tiempos razonables. Además, se amplía el espectro de posibilidades de los multicomputadores, utilizándolos para algo más que aplicaciones numéricas.Este trabajo ha sido parcialmente subvencionado por la Comisión Interministerial de Ciencia y Tecnología, bajo contrato TIC95-037

State-of-the-Art in Parallel Computing with R

R is a mature open-source programming language for statistical computing and graphics. Many areas of statistical research are experiencing rapid growth in the size of data sets. Methodological advances drive increased use of simulations. A common approach is to use parallel computing. This paper presents an overview of techniques for parallel computing with R on computer clusters, on multi-core systems, and in grid computing. It reviews sixteen different packages, comparing them on their state of development, the parallel technology used, as well as on usability, acceptance, and performance. Two packages (snow, Rmpi) stand out as particularly useful for general use on computer clusters. Packages for grid computing are still in development, with only one package currently available to the end user. For multi-core systems four different packages exist, but a number of issues pose challenges to early adopters. The paper concludes with ideas for further developments in high performance computing with R. Example code is available in the appendix

Single-Pass Memory System Evaluation for Multiprogramming Workloads

Coordinated Science Laboratory was formerly known as Control Systems LaboratoryNational Science Foundation (NSF) / MIP-8809478NCRNational Aeronautics and Space Administration (NASA) / NASA NAG 1-613Office of Naval Research / N00014-88-K-065

Jmas: A Java-based Mobile Actor System for Heterogeneous Distributed Parallel Computing

Computer Scienc

NASA high performance computing and communications program

The National Aeronautics and Space Administration's HPCC program is part of a new Presidential initiative aimed at producing a 1000-fold increase in supercomputing speed and a 100-fold improvement in available communications capability by 1997. As more advanced technologies are developed under the HPCC program, they will be used to solve NASA's 'Grand Challenge' problems, which include improving the design and simulation of advanced aerospace vehicles, allowing people at remote locations to communicate more effectively and share information, increasing scientist's abilities to model the Earth's climate and forecast global environmental trends, and improving the development of advanced spacecraft. NASA's HPCC program is organized into three projects which are unique to the agency's mission: the Computational Aerosciences (CAS) project, the Earth and Space Sciences (ESS) project, and the Remote Exploration and Experimentation (REE) project. An additional project, the Basic Research and Human Resources (BRHR) project exists to promote long term research in computer science and engineering and to increase the pool of trained personnel in a variety of scientific disciplines. This document presents an overview of the objectives and organization of these projects as well as summaries of individual research and development programs within each project

Performance Analysis of Live-Virtual-Constructive and Distributed Virtual Simulations: Defining Requirements in Terms of Temporal Consistency

This research extends the knowledge of live-virtual-constructive (LVC) and distributed virtual simulations (DVS) through a detailed analysis and characterization of their underlying computing architecture. LVCs are characterized as a set of asynchronous simulation applications each serving as both producers and consumers of shared state data. In terms of data aging characteristics, LVCs are found to be first-order linear systems. System performance is quantified via two opposing factors; the consistency of the distributed state space, and the response time or interaction quality of the autonomous simulation applications. A framework is developed that defines temporal data consistency requirements such that the objectives of the simulation are satisfied. Additionally, to develop simulations that reliably execute in real-time and accurately model hierarchical systems, two real-time design patterns are developed: a tailored version of the model-view-controller architecture pattern along with a companion Component pattern. Together they provide a basis for hierarchical simulation models, graphical displays, and network I/O in a real-time environment. For both LVCs and DVSs the relationship between consistency and interactivity is established by mapping threads created by a simulation application to factors that control both interactivity and shared state consistency throughout a distributed environment

Distributed Simulation of High-Level Algebraic Petri Nets

In the field of Petri nets, simulation is an essential tool to validate and evaluate models. Conventional simulation techniques, designed for their use in sequential computers, are too slow if the system to simulate is large or complex. The aim of this work is to search for techniques to accelerate simulations exploiting the parallelism available in current, commercial multicomputers, and to use these techniques to study a class of Petri nets called high-level algebraic nets. These nets exploit the rich theory of algebraic specifications for high-level Petri nets: Petri nets gain a great deal of modelling power by representing dynamically changing items as structured tokens whereas algebraic specifications turned out to be an adequate and flexible instrument for handling structured items. In this work we focus on ECATNets (Extended Concurrent Algebraic Term Nets) whose most distinctive feature is their semantics which is defined in terms of rewriting logic. Nevertheless, ECATNets have two drawbacks: the occultation of the aspect of time and a bad exploitation of the parallelism inherent in the models. Three distributed simulation techniques have been considered: asynchronous conservative, asynchronous optimistic and synchronous. These algorithms have been implemented in a multicomputer environment: a network of workstations. The influence that factors such as the characteristics of the simulated models, the organisation of the simulators and the characteristics of the target multicomputer have in the performance of the simulations have been measured and characterised. It is concluded that synchronous distributed simulation techniques are not suitable for the considered kind of models, although they may provide good performance in other environments. Conservative and optimistic distributed simulation techniques perform well, specially if the model to simulate is complex or large - precisely the worst case for traditional, sequential simulators. This way, studies previously considered as unrealisable, due to their exceedingly high computational cost, can be performed in reasonable times. Additionally, the spectrum of possibilities of using multicomputers can be broadened to execute more than numeric applications