A HIERARCHICAL DISTRIBUTED SHARED MEMORY PARALLEL BRANCH & BOUND APPLICATION WITH PVM AND OPENMP FOR MULTIPROCESSOR CLUSTERS

Branch&Bound (B&B) is a technique widely used to solve combinatorial optimization problems in physics and engineering science. In this paper we show how the combined use of PVM and OpenMP libraries can be a promising approach to exploit the intrinsic parallel nature of this class of application and to obtain efficient code for hybrid computational architectures. We described how both the shared memory and the distributed memory programming models can be applied to implement the same algorithm for the inter-nodes and intra-node parallelization. Some experimental tests on a local area network (LAN) of workstations are finally discussed

An occam Style Communications System for UNIX Networks

This document describes the design of a communications system which provides occam style communications primitives under a Unix environment, using TCP/IP protocols, and any number of other protocols deemed suitable as underlying transport layers. The system will integrate with a low overhead scheduler/kernel without incurring significant costs to the execution of processes within the run time environment. A survey of relevant occam and occam3 features and related research is followed by a look at the Unix and TCP/IP facilities which determine our working constraints, and a description of the T9000 transputer's Virtual Channel Processor, which was instrumental in our formulation. Drawing from the information presented here, a design for the communications system is subsequently proposed. Finally, a preliminary investigation of methods for lightweight access control to shared resources in an environment which does not provide support for critical sections, semaphores, or busy waiting, is made. This is presented with relevance to mutual exclusion problems which arise within the proposed design. Future directions for the evolution of this project are discussed in conclusion

Design and Implementation of a Distributed Version of the NASA Engine Performance Program

Distributed NEPP is a new version of the NASA Engine Performance Program that runs in parallel on a collection of Unix workstations connected through a network. The program is fault-tolerant, efficient, and shows significant speed-up in a multi-user, heterogeneous environment. This report describes the issues involved in designing distributed NEPP, the algorithms the program uses, and the performance distributed NEPP achieves. It develops an analytical model to predict and measure the performance of the simple distribution, multiple distribution, and fault-tolerant distribution algorithms that distributed NEPP incorporates. Finally, the appendices explain how to use distributed NEPP and document the organization of the program's source code

Performance measurement and analysis of PC based cluster server using SET of Architecture and modeling a scalable High performance cluster

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A versatile programming model for dynamic task scheduling on cluster computers

This dissertation studies the development of application programs for parallel and distributed computer systems, especially PC clusters. A methodology is proposed to increase the efficiency of code development, the productivity of programmers and enhance performance of executing the developed programs on PC clusters while facilitating improvement of scalability and code portability of these programs. A new programming model, named the Super-Programming Model (SPM), is created. Programs are developed assuming an instruction set architecture comprised of SuperInstructions (SIs). SPM models the target system as a large Virtual Machine (VM); VM contains functional units which are underlain with sub-computer systems and SIs are implemented with codes. When these functional units execute SIs, their codes will run on member computers to perform the corresponding operations. This approach resembles the process of designing instruction sets for microprocessors but the VM employs much coarser instructions and data structures. SIs use Super-Data Blocks (SDBs) as their operands. Each SI is assigned to a single member computer and is indivisible (i.e., its implementation is not interrupted for I/O). SIs have predictable execution times because SDB sizes are limited by predefined thresholds. These qualities of SIs help dynamic load balancing. Employing software to implement instructions makes this approach more flexible. The developed programs fit to architectures of cluster systems better. SPM provides mechanisms, such as dynamic load balancing, to assure the efficient execution of programs. The vast majority of current programming models lack such mechanisms for distributed environments that suffer from long communication latencies. Since SPM employs coarse-grain tasks, the overall management overhead is small. SDB access can often overlap the execution of other SIs; a cache system further decreases average memory latencies. Since all SDBs are virtual entities, with the runtime system support, they can be accessed in parallel and efficiently minimizes additional constraints to parallelism from underlying computer systems. In this research, a reference implementation of VM has been developed. A performance estimation model is developed that takes these features into account. Finally, the definition of scalability for parallel/distributed processing is refined to represent a multi-dimensional entity. Sample cases are analyzed

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