An Evaluation Of Java Implementations Of Message‐passing

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Adaptive Message Clustering for Distributed Agent-Based Systems

performance evaluation for implementations in SASSY with a combined RMI and shared memory message passing approach. We also show performance of our new adaptive message clustering mechanism that clusters messages when advantageous and avoids clustering when the overhead of clustering dominates. INDEX WORDS: Agent-Based Simulation, Distributed Simu-

Middleware Infrastructure for Parallel and Distributed

enhanced to support other models. The message-passing library and runtime support can be im-plemented in different ways such as pure Java implementations based on socket programming, native marshaling, and RMI [27], or by utilizing Java native interface (JNI), Java-to-C interface (JCI),

Performance Evaluation and Comparison of CORBA

The graduate project Performance Evaluation and Comparison of COREA Implementations for the Java Platform submitted by Irina K. Grant in partial fulfillment of the requirements for the degree of Master of Science in Computer and fuformation Sciences has been Approved by the graduate project committee: Date Dr. Roger'Eggen Project Director ano

Multi-agent System Simulation in Scala: An Evaluation of

evaluation of an actor model MAS framework written in the language Scala by comparing it to a comparable threaded framework. Scala is a fairly new programming language that has been in development at EPFL in Switzerland since 2003. It uses an object-functional paradigm and compiles to the JVM, which allows seamless calls to Java libraries and

Sp'21 CS Special Topics

Oct 26, 2020 Concurrency: Message Passing with Channels Unsafe Rust Assignments and evaluation: There will be 6 programming assignments, accompanied by 6 small midterms, as well as a comprehensive final exam. Prerequisites: CS361 or equivalent (for grad students), or instructor consent. Back to List

Md Firoj Ali et al, / (IJCSIT) International Journal of

efficient implementations than PVM. In MMP, all of the evaluation of message passing Ptolemy 2 It is a Java-based library to design and simulate

Java in the High Performance Computing arena: Research

java.util.concurrent.CyclicBarrier. The experimental evaluation of the hybrid Java message-passing + JOMP config-uration (being the message-passing library thread-safe) showed up to 3 times higher performancethan the equivalent pure message-passing scenario. Although JOMP scalabilityis limited to shared memory systems, its combination

Parallel Concurrent ML - Manticore

We present an empirical evaluation of the Manticore implemen-tation, which shows that it provides acceptable performance (about 2:5 slower than the single-threaded implementation). 1 In fact, almost all of the existing implementations of events have this limi-tation. The only exceptions are presumably the Haskell and Java implemen-

Accuracy Evaluation of Overlapping and Multi-resolution

optimized parallel implementations of these metrics in C++ leveraging MPI (the Message Passing Interface) and Pthreads (POSIX Threads). Among its accuracy metrics, only Average F1 score is applicable to overlapping clusterings. WebOCD [10] is an open-source RESTful web framework for the development, evaluation and analysis of overlapping

NPB-MPJ: NAS Parallel Benchmarks Implementation for Message

Performance Evaluation Summary Java for High-Performance Computing Message-Passing in Java Previous Works Message-Passing in Java Message-passing is the main HPC programming model MPJ (MPI-like bindings for Java) Implementations mpiJava. MPJ Java wrapper library over native MPI implementations (e.g. OpenMPI, MPICH). MPJ Express. MPJ pure (100%


Communication: message-passing, real-time, peer-to-peer architecture with dynamic update, load balancing and fault tolerance Mobility: strong mobility, meaning that agents can move to other Habitats during runtime, taking along their (new) Java code and state. Security policy: X.509 certification infrastructure, up to 4096-bit

Programming with Concurrency: Threads, Actors, and Coroutines

both shared memory and message passing concurrent systems using three approaches: (1) Threads in Java, (2) Actors in Scala, and (3) Coroutines in Python. Students explore the features and libraries available, and investigate the efficiency of these implementations. In this context,

High Performance Java Sockets for Parallel Computing on Clusters

In order to support efciently Java parallel applications a High Performance Java Socket implementation, named Java Fast Sockets ( JFS ), has been extended. This library was sketched in [17] and its prototype was implemented later. The work presented in this paper is the tailoring of JFS to high performance Java parallel applications on clus-ters.

Performance Evaluation of Web Services as Management Technology

Both C++ and Java implementations, apart from the NET-SNMP agent which was implemented in C Wanted to also see Java to C++ implementation differences GNU C/C++ 2.95, Java 2 SE JDK 1.3.1 versions on Linux RedHat 7.3 Two Celeron 1GHz Linux PCs with 256 Mb RAM connected through a dedicated 100 Mb/s Ethernet

Message Passing Interface

MPI (Message Passing Interface) which is the original concepts of Message Passing Java (MPJ) supports communications for distributed programs. It allows programmers to create an environment with parallel programming and shared memory. MPI is able to use some programming languages, FORTRAN, C/C++, and Java, for the implementations. The

On Implementations Issues of Parallel Computing Applications

2. Java and Numerical Computing Java has achieved rapid success because of several features such as portability, safety and pervasiveness. Java is portable at both the source (the text in a *.java) and object (the byte code *.class) format levels, which means that programs can run on any machine that has an implementation of the Java Virtual

A Status Report: Early Experiences with the implementation of

In the recent past, there has been a growing interest in developing a message passing system in Java, which resulted in a Java binding for MPI [7]. The current standard and non-standard (according to bindings defined in [7]) implementations primarily follow three approaches. The first approach uses

A Parallel Implementation of the Finite-Domain Time

The performance evaluation of the Java version revealed that it could achieve comparable performance to the original C code. In this paper, we implement a parallel version of the Finite-Difference Time-Domain (FDTD) method in Java. WeusedMPJExpress[2] athread-safeimplementationof Message Passing Interface (MPI) [6] bindings in Java to

Performance Analysis of Java Message-Passing Libraries on

Two main types of implementations of Message-Passing for Java: Java wrapper provides efficient MPI communication through calling native methods using JNI. The major drawback is lack of portability Pure Java provides a portable message-passing implementation since the whole library is developed in Java, although the communication is less efficient

Virtual Machines 76b0fa668c1cd016096eb9bc1bfde44a

May 15, 2021 Message Passing InterfaceJava and the Java Virtual evaluation, and performance of and implementations of PVM/MPI; parallel

M-JavaMPI: A Java-MPI Binding with Process Migration Support

Keywords: process migration, MPI, JVMDI, message passing, M-JavaMPI, load balancing, Java, cluster computing, parallel computing 1. Introduction The Message Passing Interface (MPI) is a widely adopted communication library for parallel and distributed computing. It provides an infrastructure for users to build high performance distributed computing

FastMPJ: a Scalable and E cient Java Message-Passing Library

FastMPJ: a Scalable and Efficient Java Message-Passing Libra ry 3 3RelatedWork Multiple MPI native implementations have been devel-oped, improved and maintained over the last 15 years intended for cluster, grid and emerging cloud comput-ing environments. Regarding MPJ libraries, there have been several efforts to develop a Java message-passing


Existing˜approaches˜to˜MPI˜for˜Java˜can˜be˜grouped˜ into˜two˜main˜types:˜(1)˜native˜MPI˜bindings˜where˜the˜ some˜ native˜ MPI˜ library˜ is˜ called˜ by˜ Java˜ programs˜ through˜ Java˜ wrappers˜ [9,10,11],˜ and˜ (2)˜ pure˜ Java˜ implementations˜ [13,14].˜ The˜ native˜ MPI˜ binding˜

Evaluating Java Runtime Reflection for Implementing Cross

and the design impact of alternative implementations of cross-language method invocations for the object-oriented scripting lan-guage Frag, implemented and embedded in Java. In particular, we compare reflective integration and generative integration tech-niques. For that, we present a performance evaluation based on a large set of test cases.

Design of efficient Java message-passing collectives on multi

for message-passing libraries. With respect to Java, there have been several implementations of Java message-passing libraries since its introduction [1]. Although initially each project developed their own MPI-like binding for the Java language, current projects generally adhere

Enabling High Performance Computing for Java Applications by

different MPI implementations. Keywords: Parallelisation, Message-Passing Interface, Java, High Performance Computing. 1 Introduction Java is an object-oriented, general-purpose, concurrent, class-based, and object-oriented programming language which was first introduced 1995. Thanks to the

Experimental Analysis of Distributed Graph Systems

(Java or C++). It is common knowledge that C++ has better overall performance than Java for multiple reasons. Although we are not aware of a system that has both C++ and Java implementations to conduct a more controlled ex-periment, the fact that GraphLab and Giraph have similar performance when they use the same partitioning algorithm

Implementation and performance evaluation of parallel FFT

algorithms listed are implemented in the sequential and MPI (message passing interface) parallel forms and their performances are compared. The algorithms are implemented in two parallel styles of algorithms such that we reduce communication overhead. We also see the effect of the inter-connection network on the performance of the algorithms. 1.

Design and implementation of Java bindings in Open MPI

This paper describes the Java MPI bindings that have been included in the Open MPI distribution. Open MPI is one of the most popular implementations of MPI, the Message-Passing Interface, which is the predominant programming paradigm for parallel applications on distributed memory computers. We have added Java support to Open MPI,

Evaluation of Java Message Passing in High Performance Data

Interfaces (API) for Java message passing mpiJava 1.2 [12] and Java Grande Forum (JGF) Message Passing interface for Java (MPJ) [13]. However, there are implementations that [9]. Performance of Java MPI support has been studied with different implementations and recently in [11, 14]. The focus of

Java in the High Performance Computing Arena: Research

Java, High Performance Computing, Performance Evaluation, Multi-core Architectures, Message-passing, Threads, Cluster, InfiniBand 1. Introduction Java has become a leading programming language soon after its release, especially in web-based and distributed computing environments,and it is an emerging option for High Performance Computing (HPC

DXNet: Scalable Messaging for Multi-Threaded Java

cient message passing for primitive, derived, vector and indexed data types [17]. As MPI's ofcial support is limited to C, C++ and Fortran, Java object serialization is not consid-ered by the standard. Nevertheless, MPI is available for Java applications through implementations of the MPI standard in Java [18] or wrappers of a native library [19].

Lecture 6: Message Passing Interface

+Implementations for F77, C and C++ are freely downloadable − Kitchen-sink functionality, makes it hard to learn all (unnecessary: a bare dozen are needed in most cases) −Implementations on shared-memory machines is often quite poor, and does not suit the programming model −Has rivals in other message-passing libraries (e.g. PVM)

Non-blocking Java Communications Support on Clusters

Introduction Design Implementation Evaluation Conclusions Introduction Previous work: Non-blocking communication support Java NIO (New I/O) Improves scalability, basic in client/server applications Message-Passing Java mpiJava, wrapper to native MPI implementation that supports non-blocking comms.

Evaluation of Java Message Passing in High Performance Data

Interfaces (API) for Java message passing mpiJava 1.2 [13] and Java Grande Forum (JGF) Message Passing interface for Java (MPJ) [14]. However, there are implementations that follow custom API as well [9]. Performance of Java MPI support has been studied with different implementations and recently in [12, 15]. The focus of

A Study of Java Networking Performance on a Linux Cluster

research projects have built MPI related systems that support Java in some way. Many of these have attempted to provide Java bindings to underlying MPI [8][9][10] implementations. However, there are growing research efforts to provide a pure Java message-passing infrastructure [11][12].

NPB-MPJ: NAS Parallel Benchmarks Implementation for Message

Moreover, the availability of different Java parallel pro-gramming libraries, such as Message-Passing in Java (MPJ) libraries and ProActive [2] [3], an RMI-based middleware for multithreaded and distributed computing focused on Grid applications, eases Java s adoption. In this scenario, a com-parative evaluation of Java for parallel computing

Message passing Implementation for Process Functional Language

programs [6]. Currently we have three generators from PFL a generator to Java, Haskell and C++ with support for Message Passing Interface [8] and extend PFL to work in distributed environment. The goal of MPI is to develop a widely used standard for writing message passing programs.

F-MPJ: scalable Java message-passing communications on

F-MPJ: scalable Java message-passing communications tives, and also a kernel/application benchmarking. Finally, Sect. 7 concludes the pa-per. 2 Related work Since the introduction of Java, there have been several implementations of Java mes-saging libraries for HPC [15]. These libraries have followed different implementation