Java for parallel computing and as a general language for scientific and engineering simulation and modeling

Fox, Geoffrey; Furmański, W.

doi:10.1002/(sici)1096-9128(199706)9:6<415::aid-cpe299>3.0.co;2-v

Cited by 33 publications

(19 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In a logic program, knowledge is represented by a set of facts and rules used to describe relationships between data objects. Java [11] is an Internet programming language derived from C++ with additional support for multimedia display and portability over the Internet [5,8,10]. Java has also been interfaced with web browsers, and is being used extensively over the Internet for multimedia presentation.…”

Section: Background and Definitionsmentioning

confidence: 99%

“…A try_me_else label L 10 is also placed on the stack to handle failure. Upon backtracking, the control is transferred to the label L 10 . The receive_bindings instruction is used to report the bindings for the goal arguments from each eligible server.…”

Section: An Execution Trace Of the Coordinatormentioning

confidence: 99%

“…There is also work on using Java as a web based parallel language for cluster based multimedia computing [5,8,10] and as an interface with high performance Fortran programming. The goal of this project is to use Java in combination with message passing libraries such as PVM [26] and MPI [13] to treat the web as a large cluster based virtual computer.…”

Section: Related Workmentioning

confidence: 99%

“…Coarse grain data parallelism is present since multiple knowledge bases are present on different clusters, and each cluster concurrently solves a goal. Object level massive parallelism [10] is present since multiple individual components are simulated simultaneously. A coordinator is used to manage and collect data from multiple servers, while major processing is done within the servers to reduce data transfer overhead.…”

mentioning

confidence: 99%

See 3 more Smart Citations

A Scalable Distributed Multimedia Knowledge Retrieval System on a Cluster of Heterogeneous High Performance Architectures

Ryan

Bansal

2000

Int. J. Artif. Intell. Tools

View full text Add to dashboard Cite

This paper describes a system to distribute and retrieve multimedia knowledge on a cluster of heterogeneous high performance architectures distributed over the Internet. The knowledge is represented using facts and rules in an associative logic-programming model. Associative computation facilitates distribution of facts and rules, and exploits coarse grain data parallel computation. Associative logic programming uses a flat data model that can be easily mapped onto heterogeneous architectures. The paper describes an abstract instruction set for the distributed version of the associative logic programming and the corresponding implementation.The implementation uses a message-passing library for architecture independence within a cluster, uses object oriented programming for modularity and portability, and uses Java as a front-end interface to provide a graphical user interface and multimedia capability and remote access via the Internet. The performance results on a cluster of IBM RS 6000 workstations are presented. The results show that distribution of data improves the performance almost linearly for small number of processors in a cluster.

show abstract

Section: Background and Definitionsmentioning

confidence: 99%

Section: An Execution Trace Of the Coordinatormentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

A Scalable Distributed Multimedia Knowledge Retrieval System on a Cluster of Heterogeneous High Performance Architectures

Ryan

Bansal

2000

Int. J. Artif. Intell. Tools

View full text Add to dashboard Cite

show abstract

“…Examples include integration of collaboration into HPcc; the natural synergy of distribution simulation and the HLA standard with our architecture [2]; and the step from object to visual component based programming [3] in parallel and distributed computing. Finally we discuss the use of DcciS to build parallel programming environments and HPJavathe use of Java on parallel or sequential machines for high performance computing [4,5].…”

Section: Introductionmentioning

confidence: 99%

Parallel and Distributed Computing using Pervasive Web and Object Technologies

Fox

Furmański

1998

Advances in Parallel Computing

Self Cite

View full text Add to dashboard Cite

We review the growing power and capability of commodity computing and communication technologies largely driven by commercial distributed information systems. These systems are built from CORBA, Microsoft's COM, Javabeans, and less sophisticated web and networked approaches. One can abstract these to a three-tier model with largely independent clients connected to a distributed network of servers. The latter host various services including object and relational databases and, of course, parallel and sequential computing. High performance can be obtained by combining concurrency at the middle-server tier with optimized parallel back-end services. The resultant system combines the needed performance for large-scale HPCC applications with the rich functionality of commodity systems. Further, the architecture with distinct interface, server and specialized service implementation layers, naturally allows advances in each area to be easily incorporated. We show that this approach can be applied to both metacomputing and to provide improved parallel programming environments. We describe exploitation issues within a CORBA context and illustrate how performance can be obtained within a commodity architecture. Examples are given from collaborative systems, support of multidisciplinary interactions, proposed visual HPCC ComponentWare, distributed simulation, and the use of Java in high-performance computing.

show abstract

Javelin: Internet-based parallel computing using Java

Christiansen

Cappello

Ionescu

et al. 1997

Concurrency: Pract. Exper.

135

View full text Add to dashboard Cite

Java offers the basic infrastructure needed to integrate computers connected to the Internet into a seamless parallel computational resource: a flexible, easily-installed infrastructure for running coarsegrained parallel applications on numerous, anonymous machines. Ease of participation is seen as a key property for such a resource to realize the vision of a multiprocessing environment comprising thousands of computers.We present Javelin, a Java-based infrastructure for global computing. The system is based on Internet software technology that is essentially ubiquitous: Web technology. Its architecture and implementation require participants to have access only to a Java-enabled Web browser. The security constraints implied by this, the resulting architecture, and current implementation are presented. The Javelin architecture is intended to be a substrate on which various programming models may be implemented. Several such models are presented: A Linda Tuple Space, an SPMD programming model with barriers, as well as support for message passing. Experimental results are given in the form of micro-benchmarks and a Mersenne Prime application that runs on a heterogeneous network of several parallel machines, workstations, and PCs.

show abstract

Java for parallel computing and as a general language for scientific and engineering simulation and modeling

Cited by 33 publications

References 16 publications

A Scalable Distributed Multimedia Knowledge Retrieval System on a Cluster of Heterogeneous High Performance Architectures

A Scalable Distributed Multimedia Knowledge Retrieval System on a Cluster of Heterogeneous High Performance Architectures

Parallel and Distributed Computing using Pervasive Web and Object Technologies

Javelin: Internet-based parallel computing using Java

Contact Info

Product

Resources

About