Parallel Access to Persistent Multidimensional Arrays from HPF Applications Using Panda
A critical performance issue for a number of scientific and engineering applications is the efficient transfer of data to secondary storage. Languages such as High Performance Fortran (HPF) have been introduced to allow programming distributed-memory systems at a relatively high level of abstraction. However, the present version of HPF does not provide appropriate constructs for controlling the parallel I/O capabilities of these systems. In this paper, constructs to specify parallel I/O operations on multidimensional arrays in the context of HPF are proposed. The paper also presents implementation concepts that are based on the HPF compiler developed at the University of Vienna and the parallel I/O runtime system Panda developed at the University of Illinois. Experimental performance results are discussed in the context of financial management and traffic simulation applications.
KeywordsPension Fund Language Construct Simulation Application Secondary Storage Application Case Study
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