WWW Programming using computational logic systems (and the PiLLoW/Ciao library)

We discuss from a practical point of view a number of issues involved in writing Internet and WWW applications using LP/CLP systems. We describe Pd_l_oW, a public-domain Internet and WWW programming library for LP/CLP systems which we argüe significantly simplifies the process of writing such applications. Pd_l_oW provides facilities for generating HTML structured documents, producing HTML forms, writing form handlers, accessing and parsing WWW documents, and accessing code posted at HTTP addresses. We also describe the architecture of some application classes, using a high-level model of client-server interaction, active modules. We then propose an architecture for automatic LP/CLP code downloading for local execution, using generic browsers. Finally, we also provide an overview of related work on the topic. The PiLLoW library has been developed in the context of the &- Prolog and CIAO systems, but it has been adapted to a number of popular LP/CLP systems, supporting most of its functionality

Parallel Computing for Probabilistic Response Analysis of High Temperature Composites

The objective of this Phase I research was to establish the required software and hardware strategies to achieve large scale parallelism in solving PCM problems. To meet this objective, several investigations were conducted. First, we identified the multiple levels of parallelism in PCM and the computational strategies to exploit these parallelisms. Next, several software and hardware efficiency investigations were conducted. These involved the use of three different parallel programming paradigms and solution of two example problems on both a shared-memory multiprocessor and a distributed-memory network of workstations

Parallel Programming Using Shared Objects and Broadcasting

The two major design approaches taken to build distributed and parallel computer systems, multiprocessing and multicomputing, are discussed. A model that combines the best properties of both multiprocessor and multicomputer systems, easy-to-build hardware, and a conceptually simple programming model is presented. Using this model, a programmer defines and invokes operations on shared objects, the runtime system handles reads and writes on these objects, and the reliable broadcast layer implements indivisible updates to objects using the sequencing protocol. The resulting system is easy to program, easy to build, and has acceptable performance on problems with a moderate grain size in which reads are much more common than writes. Orca, a procedural language whose sequential constructs are roughly similar to languages like C or Modula 2 but which also supports parallel processes and shared objects and has been used to develop applications for the prototype system, is described

Programming a Distributed System Using Shared Objects

Building the hardware for a high-performance distributed computer system is a lot easier than building its software. The authors describe a model for programming distributed systems based on abstract data types that can be replicated on all machines that need them. Read operations are done locally, without requiring network traffic. Writes can be done using a reliable broadcast algorithm if the hardware supports broadcasting; otherwise, a point-to-point protocol is used. The authors have built such a system based on the Amoeba microkernel, and implemented a language, Orca, on top of it. For Orca applications that have a high ratio of reads to writes, they measure good speedups on a system with 16 processors

Replication Techniques for Speeding up Parallel Applications on Distributed Systems

This paper discusses the design choices involved in replicating objects and their effect on performance. Important issues are: how to maintain consistency among different copies of an object; how to implement changes to objects; and which strategy for object replication to use. We have implemented several options to determine which ones are most efficient

MATLAB*G: A Grid-Based Parallel MATLAB

This paper describes the design and implementation of MATLAB*G, a parallel MATLAB on the ALiCE Grid. ALiCE (Adaptive and scaLable internet-based Computing Engine), developed at NUS, is a lightweight grid-computing middleware. Grid applications in ALiCE are written in Java and use the distributed shared memory programming model. Utilizing existing MATLAB functions, MATLAB*G provides distributed matrix computation to the user through a set of simple commands. Currently two forms of parallelism for distributed matrix computation are implemented: task parallelism and job parallelism. Experiments are carried out to investigate the performance of MATLAB*G on each type of parallelism. Results indicate that for large matrix sizes MATLAB*G can be a faster alternative to sequential MATLAB.Singapore-MIT Alliance (SMA

The Pacifican, October 15 ,1982

https://scholarlycommons.pacific.edu/pacifican/3452/thumbnail.jp

The Cowl - v.58 - n.1 - Sep 23, 1993

The Cowl - student newspaper of Providence College. Volume 58, Number 1 - September 23, 1993. 24 pages