Traditional parallelprogramming styles have man), problems which hinder the development of parallel applications. The message passing style can be too complex for many programmers. While shared memory based parallel ...
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ISBN:
(纸本)9780769528335
Traditional parallelprogramming styles have man), problems which hinder the development of parallel applications. The message passing style can be too complex for many programmers. While shared memory based parallelprogramming is relatively easy, it requires programmers to guarantee there is no data race in programs by using mutually exclusive locks. Data race conditions are generally difficult to debug and difficult to prevent as well. The view-oriented parallel programming (VOPP) is a novel shared-memory-based programming style. It removes the burden of guaranteeing data race free from the programmers. With the VOPP approach, shared data objects in a parallel program are divided into views according to the memory access pattern of the parallel algorithm. Data race is not an issue in VOPP since mutual exclusion is automatically,, done by the underlying system when a view is accessed. The programmer only needs to synchronize the access of views using synchronization primitives like barriers. By removing data races of view access, VOPP makes it easier to code and less difficult to debug programs. It provides potential performance advantages on multi-core systems as well as cluster computers. It will also provide useful information for efficient implementation of transactional memory.
This paper evaluates the performance of a novel Yew-orientedparallelprogramming style for parallelprogramming on cluster computers. view-oriented parallel programming is based on Distributed Shared Memory which is ...
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ISBN:
(纸本)0769523803
This paper evaluates the performance of a novel Yew-orientedparallelprogramming style for parallelprogramming on cluster computers. view-oriented parallel programming is based on Distributed Shared Memory which is friendly and easy for programmers to use. It requires the programmer to divide shared data into views according to the memory access pattern of the parallel algorithm. One of the advantages of this programming style is that it offers the performance potential for the underlying Distributed Shared Memory system to optimize consistency maintenance. Also it allows the programmer to participate in performance optimization of a program through wise partitioning of the shared data into views. Experimental results demonstrate a significant performance gain of the programs based on the view-oriented parallel programming style.
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