Vcluster: A Portable Virtual Computing Library For Cluster Computing

Message passing has been the dominant parallel programming model in cluster computing, and libraries like Message Passing Interface (MPI) and Portable Virtual Machine (PVM) have proven their novelty and efficiency through numerous applications in diverse areas. However, as clusters of Symmetric Multi-Processor (SMP) and heterogeneous machines become popular, conventional message passing models must be adapted accordingly to support this new kind of clusters efficiently. In addition, Java programming language, with its features like object oriented architecture, platform independent bytecode, and native support for multithreading, makes it an alternative language for cluster computing. This research presents a new parallel programming model and a library called VCluster that implements this model on top of a Java Virtual Machine (JVM). The programming model is based on virtual migrating threads to support clusters of heterogeneous SMP machines efficiently. VCluster is implemented in 100% Java, utilizing the portability of Java to address the problems of heterogeneous machines. VCluster virtualizes computational and communication resources such as threads, computation states, and communication channels across multiple separate JVMs, which makes a mobile thread possible. Equipped with virtual migrating thread, it is feasible to balance the load of computing resources dynamically. Several large scale parallel applications have been developed using VCluster to compare the performance and usage of VCluster with other libraries. The results of the experiments show that VCluster makes it easier to develop multithreading parallel applications compared to conventional libraries like MPI. At the same time, the performance of VCluster is comparable to MPICH, a widely used MPI library, combined with popular threading libraries like POSIX Thread and OpenMP. In the next phase of our work, we implemented thread group and thread migration to demonstrate the feasibility of dynamic load balancing in VCluster. We carried out experiments to show that the load can be dynamically balanced in VCluster, resulting in a better performance. Thread group also makes it possible to implement collective communication functions between threads, which have been proved to be useful in process based libraries

Java on Networks of Workstations (JavaNOW): A Parallel Computing Framework Inspired by Linda and the Message Passing Interface (MPI)

Networks of workstations are a dominant force in the distributed computing arena, due primarily to the excellent price/performance ratio of such systems when compared to traditionally massively parallel architectures. It is therefore critical to develop programming languages and environments that can help harness the raw computational power available on these systems. In this article, we present JavaNOW (Java on Networks of Workstations), a Java‐based framework for parallel programming on networks of workstations. It creates a virtual parallel machine similar to the MPI (Message Passing Interface) model, and provides distributed associative shared memory similar to the Linda memory model but with a richer set of primitive operations. JavaNOW provides a simple yet powerful framework for performing computation on networks of workstations. In addition to the Linda memory model, it provides for shared objects, implicit multithreading, implicit synchronization, object dataflow, and collective communications similar to those defined in MPI. JavaNOW is also a component of the Computational Neighborhood, a Java‐enabled suite of services for desktop computational sharing. The intent of JavaNOW is to present an environment for parallel computing that is both expressive and reliable and ultimately can deliver good to excellent performance. As JavaNOW is a work in progress, this article emphasizes the expressive potential of the JavaNOW environment and presents preliminary performance results only

Scalability study of virtual parallel processing systems

Orientador: Marco Aurélio Amaral HenriquesDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de ComputaçãoResumo: A utilização de sistemas de processamento paralelo virtual tem aumentado em várias áreas de aplicação, desde as estritamente matemáticas até as médicas e biológicas. Devido a esse crescimento, são cada vez mais necessários mecanismos para uma avaliação consistente de desempenho de sistemas desse tipo. É necessário também haver um entendimento mais preciso do conceito de escalabilidade, um dos principais indicadores de desempenho, tanto quanto ao seu significado como quanto à maneira de mensurá-la. Este trabalho traz um estudo comparativo sobre métricas de escalabilidade para sistemas de processamento paralelo homogêneos e heterogêneos, onde duas métricas homogêneas foram selecionadas para serem utilizadas na avaliação do limite superior de escalabilidade de duas plataformas de processamento paralelo virtual (JoiN a JPVM). A partir deste estudo foi proposta uma métrica de escalabilidade que utiliza como base para a sua análise o speedup, conceito muito familiar em processamento paralelo. Foram realizados testes de validação da métrica proposta, que destacam seu caráter prático e adequação para a aplicação em sistemas heterogêneos de processamento paralelo virtualAbstract: The utilization of Virtual Parallel Processing Systems has increased in several application areas, from strictly mathematical to medical and biological areas. Due to this increasing, mechanisms that offer a consistent performance evaluation of these systems, became more important and useful. It is also important to understand the concept of scalability, one of the main performance pointers, and the way of measuring it. This work shows a comparative study about scalability metrics of homogeneous and heterogeneous parallel processing systems, where two of the homogeneous metrics, were selected to evaluate the scalability upper limit on two virtual parallel processing platforms (JoiN and JPVM). As a result, We proposed a new scalability metric, which is based on the speedup, a well known parallel processing concept. Validation tests were performed using the proposed metric, which highlight its characteristics and suitability to heterogeneous virtual parallel processing systemsMestradoEngenharia de ComputaçãoMestre em Engenharia Elétric