Efficient Java Communication Protocols on High-speed Cluster Interconnects

Taboada, Guillermo L.; Touriño, Juan; Doallo, Ramón

doi:10.1109/lcn.2006.322110

Cited by 4 publications

(2 citation statements)

References 23 publications

(19 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Fortunately, the stigma of Java being a low performance language has abated with improvements in its Just In Time compilers and improved garbage collector implementations, as well as new advanced IO and communication libraries. Java libraries such as Java Fast Sockets (JFS) [34] also exist to allow users to take advantage of advanced high performance communication interconnects that were previously unavailable to Java developers. This has lead to the creation of new parallel communication tools for Java.…”

Section: Java and Parallel Computingmentioning

confidence: 99%

Parallel computing in enterprise modeling.

Goldsby¹,

Armstrong²,

Shneider³

et al. 2008

View full text Add to dashboard Cite

This report presents the results of our efforts to applly high-performance computing to entitybased simulations with a multi-use plugin for parallel computing. We use the term 'Entity-based simulation' to describe a class of simulaton which includes both discrete event simulation and agent based simulation. What simulations of this class share, and what differs from more traditional models, is that the result sought is emergent from a large number of contributing entities. Logistic, economic and social simulations are members of this class where things or people are organized or self-organize to produce a solution. Entity-based problems never have an a priori ergodic principle that will greatly simplify calculations. Because the results of entity-based simulations can only be realized at scale, scalable computing is de rigueur for large problems. Having said that, the absence of a spatial organizing principal makes the decomposition of the problem onto processors problematic. In addition, practitioners in this domain commonly use the Java programming language which presents its own problems in a high-performance setting. The plugin we have developed, called the Parallel Particle Data Model, overcomes both of these obstacles and is now being used by two Sandia frameworks: the Decision Analysis Center, and the Seldon social simulation facility. While the ability to engage U.S.-sized problems is now available to the Decision Analysis Center, this plugin is central to the success of Seldon. Because Seldon relies on computationally intensive cognitive sub-models, this work is necessary to acheive the scale necessary for realistic results. With the recent upheavals in the financial markets, and the inscrutability of terrorist activity, this simulation domain will likely need a capability with ever greater fidelity. High-performance computing will play an important part in enabling that greater fidelity..

show abstract

Section: Java and Parallel Computingmentioning

confidence: 99%

Parallel computing in enterprise modeling.

Goldsby¹,

Armstrong²,

Shneider³

et al. 2008

View full text Add to dashboard Cite

show abstract

“…The transport overhead can be reduced through the use of a high performance Java sockets implementation, named Java Fast Sockets (JFS) [16]. JFS provides with high performance network support on Java (currently SCI support) as it increases communication performance avoiding unnecessary copies and buffering and the cost of primitive data type array serialization, the process of transforming the arrays in stream bytes to send across the network.…”

Section: High Performance Sockets Supportmentioning

confidence: 99%

High Performance Java Remote Method Invocation for Parallel Computing on Clusters

Taboada

Teijeiro

Touriño

2007

2007 IEEE Symposium on Computers and Communications

Self Cite

View full text Add to dashboard Cite

This paper presents a more efficient Java Remote Method Invocation (RMI) implementation for high-speed clusters. The use of Java for parallel programming on clusters is limited by the lack of efficient communication middleware and high-speed cluster interconnect support. This implementation overcomes these limitations through a more efficient Java RMI protocol based on several basic assumptions on clusters. Moreover, the use of a high performance sockets library provides with direct high-speed interconnect support. The performance evaluation of this middleware on a Gigabit Ethernet (GbE) and a Scalable Coherent Interface (SCI) cluster shows experimental evidence of throughput increase. Moreover, qualitative aspects of the solution such as transparency to the user, interoperability with other systems and no need of source code modification can augment the performance of existing parallel Java codes and boost the development of new high performance Java RMI applications.

show abstract