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  • 1
    Publication Date: 1999-01-01
    Description: Since the introduction of the Java programming language, there has been widespread interest in the use Java for the high performance scientific computing. One major impediment to such use is the performance penalty paid relative to Fortran. To support our research on overcoming this penalty through compiler technology, we have developed a benchmark suite, called OwlPack, which is based on the popular LINPACK library. Although there are existing implementations of LINPACK in Java, most of these are produced by direct translation from Fortran. As such they do not reflect the style of programming that a good object‐oriented programmer would use in Java. Our goal is to investigate how to make object‐oriented scientific programming practical. Therefore we developed two object‐oriented versions of LINPACK in Java, a true polymorphic version and a “Lite” version designed for higher performance. We used these libraries to perform a detailed performance analysis using several leading Java compilers and virtual machines, comparing the performance of the object‐oriented versions of the benchmark with a version produced by direct translation from Fortran. Although Java implementations have been made great strides, they still fall short on programs that use the full power of Java’s object‐oriented features. Our ultimate goal is to drive research on compiler technology that will reward, rather than penalize good object‐oriented programming practice.
    Print ISSN: 1058-9244
    Electronic ISSN: 1875-919X
    Topics: Computer Science , Media Resources and Communication Sciences, Journalism
    Published by Hindawi
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  • 2
    Publication Date: 2010-01-01
    Description: We introduce the Concurrent Collections (CnC) programming model. CnC supports flexible combinations of task and data parallelism while retaining determinism. CnC is implicitly parallel, with the user providing high-level operations along with semantic ordering constraints that together form a CnC graph. We formally describe the execution semantics of CnC and prove that the model guarantees deterministic computation. We evaluate the performance of CnC implementations on several applications and show that CnC offers performance and scalability equivalent to or better than that offered by lower-level parallel programming models.
    Print ISSN: 1058-9244
    Electronic ISSN: 1875-919X
    Topics: Computer Science , Media Resources and Communication Sciences, Journalism
    Published by Hindawi
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
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