Abstract—High Performance Computing (HPC) provides support to run advanced application programs efficiently. Java adaptation in HPC has become an apparent choice for new endeavors, because of its significant characteristics. These include object-oriented, platform independent, portable, secure, built-in networking, multithreading, and an extensive set of Application Programming Interfaces (APIs). Consequently multi-core systems and multi-core programming tools are becoming popular. However, today the leading HPC programming model is Message Passing Interface (MPI). In present day computing, while writing a parallel program for multi-core systems in distributed environment may deploy an approach where both shared and distributed memory models are used. Moreover an interoperable, asynchronous, and reliable working environment is required for programmers and researchers to build the HPC applications. This paper reviews the existing MPI implementations in Java. Several assessment parameters are identified to analyze the Java based MPI models; including their strengths and weaknesses.
Keywords-HPC; Java; message passing; MPI
I. INTRODUCTION
Nowadays, there is a persistent demand for greater computational power to process large amount of data. HPC makes previously unachievable calculations possible. Today the modern computer architectures are relying more and more upon hardware level parallelism. They attain computing performance, through realization of multiple execution units, pipelined instructions [1] and multiple CPU cores [2]. The largest and fastest computers use both shared and distributed memory architectures. Contemporary trends show that the hybrid type of memory architectures will continue to prevail [3].
Modern practice...
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To empower applications and the OS to scale, fos consolidates a few methodologies. To begin with, the OS is calculated by administration being given. By calculating by framework administration, scalability is expanded in light of the fact that each one administration can run freely. In the wake of calculating by administration, each one administration is figured again into an armada of spatially dispersed servers. Every server inside an armada executes all alone's core along these lines expanding the parallelism accessible. By spatially appropriating framework servers, territory can be misused by both decreasing correspondence cost and expanding information access region. A given OS administration is made
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