• Refine Query
  • Source
  • Publication year
  • to
  • Language
  • 8
  • Tagged with
  • 8
  • 8
  • 8
  • 7
  • 6
  • 6
  • 4
  • 4
  • 4
  • 3
  • 2
  • 2
  • 2
  • 2
  • 2
  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Behavioural model debugging in Linda

Sewry, David Andrew January 1994 (has links)
This thesis investigates event-based behavioural model debugging in Linda. A study is presented of the Linda parallel programming paradigm, its amenability to debugging, and a model for debugging Linda programs using Milner's CCS. In support of the construction of expected behaviour models, a Linda program specification language is proposed. A behaviour recognition engine that is based on such specifications is also discussed. It is shown that Linda's distinctive characteristics make it amenable to debugging without the usual problems associated with paraUel debuggers. Furthermore, it is shown that a behavioural model debugger, based on the proposed specification language, effectively exploits the debugging opportunity. The ideas developed in the thesis are demonstrated in an experimental Modula-2 Linda system.
2

A distributed Linda server on a network of heterogeneous processors

Smith, Graham Leslie January 1993 (has links)
Linda is an approach to parallelism which relies on a virtual associative shared memory called tuple space. Tuple space is accessed through a small set of primitive operations and is conceptually easy to understand and manipulate. The physical implementation of a Linda tuple space may of course be completely different from the conceptual model. Rhodes has implemented versions of Linda on a ring of RS-232 joined PC's and on a cluster of T800 transputers with a single copy of tuple space on one transputer. Current research targets the implementation of a distributed Linda server on a network of heterogeneous processors. This work describes the design and implementation of a distributed Linda server. Emphasis is placed on aspects of the design which enhance portability and efficiency.
3

Analyzing communication flow and process placement in Linda programs on transputers

De-Heer-Menlah, Frederick Kofi 28 November 2012 (has links)
With the evolution of parallel and distributed systems, users from diverse disciplines have looked to these systems as a solution to their ever increasing needs for computer processing resources. Because parallel processing systems currently require a high level of expertise to program, many researchers are investing effort into developing programming approaches which hide some of the difficulties of parallel programming from users. Linda, is one such parallel paradigm, which is intuitive to use, and which provides a high level decoupling between distributable components of parallel programs. In Linda, efficiency becomes a concern of the implementation rather than of the programmer. There is a substantial overhead in implementing Linda, an inherently shared memory model on a distributed system. This thesis describes the compile-time analysis of tuple space interactions which reduce the run-time matching costs, and permits the distributon of the tuple space data. A language independent module which partitions the tuple space data and suggests appropriate storage schemes for the partitions so as to optimise Linda operations is presented. The thesis also discusses hiding the network topology from the user by automatically allocating Linda processes and tuple space partitons to nodes in the network of transputers. This is done by introducing a fast placement algorithm developed for Linda. / KMBT_223
4

Distribution of Linda across a network of workstations /

Schumann, Charles N., January 1993 (has links)
Thesis (M.S.)--Virginia Polytechnic Institute and State University, 1993. / Vita. Abstract. Includes bibliographical references (leaves 147-155). Also available via the Internet.
5

Remora : implementing adaptive parallelism on a heterogeneous cluster of networked workstations

Rehmet, Geoffrey Michael January 1995 (has links)
Computers connected to a local area network are often only fully utilized for short periods of time. In fact, most workstations are not used at all for a significant portion of the day. The combined "idle time" of the workstations on a network constitutes a significant computing resource, which is generally wasted. If harnessed properly, such a resource could constitute a cheap alternative to expensive high-performance computers. Adaptive parallelism refers to the parallel execution of a computation on a dynamically changing set of processors. This thesis investigates the viability of this approach as a vehicle to harness the "idle cycles" available on a heterogeneous cluster of networked computers. A system, called Remora, which implements adaptive parallelism via the Linda programming paradigm, is presented. Experiments, performed using Remora, show that adaptive parallelism provides an efficient vehicle for using idle processor cycles, without having an adverse effect on the tasks which constitute the normal workload of the computers being used.
6

The role of parallel computing in bioinformatics /

Akhurst, Timothy John. January 2005 (has links)
Thesis (M. Sc. (Biochemistry, Microbiology and Biotechnology))--Rhodes University, 2005. / Research report submitted in partial fulfilment of the requirements for the degree of Master of Science.
7

The role of parallel computing in bioinformatics

Akhurst, Timothy John January 2005 (has links)
The need to intelligibly capture, manage and analyse the ever-increasing amount of publicly available genomic data is one of the challenges facing bioinformaticians today. Such analyses are in fact impractical using uniprocessor machines, which has led to an increasing reliance on clusters of commodity-priced computers. An existing network of cheap, commodity PCs was utilised as a single computational resource for parallel computing. The performance of the cluster was investigated using a whole genome-scanning program written in the Java programming language. The TSpaces framework, based on the Linda parallel programming model, was used to parallelise the application. Maximum speedup was achieved at between 30 and 50 processors, depending on the size of the genome being scanned. Together with this, the associated significant reductions in wall-clock time suggest that both parallel computing and Java have a significant role to play in the field of bioinformatics.
8

Distribution of Linda across a network of workstations

Schumann, Charles N. 10 November 2009 (has links)
The Linda programming language provides an architecturally independent paradigm for writing parallel programs. By designing and implementing Linda on a network of stand alone workstations a scalable multicomputer can be constructed from existing equipment. This thesis presents the design, implementation and testing of a distributable Linda kernel and communications subsystem providing a framework for full distribution of Linda on a network of workstations. Following a presentation of the Linda language, the kernel’s design and rationale are presented. The design provides for interprocess communications by implementing a protocol on top of the Unix socket facility. Choosing sockets as the interprocess communications medium has the advantage of wide portability. However, a design critique is presented which addresses several disadvantages of the socket based communications model. Considerable attention is given to quantifying the effectiveness of this design in comparison to a shared memory, non-distributable design from Yale University. A thorough investigation into the source of particular observed phenomena is presented which leads to an improvement in wall time performance of an order of magnitude. / Master of Science

Page generated in 0.0629 seconds