Gabriel, Edgar2013-12-022013-12-02August 2012013-08http://hdl.handle.net/10657/468I/O is a major time-limiting factor in high performance computing (HPC) applications. The combined effects of hard drive latency and bandwidth make I/O the slowest operation in a system. A lot of work has been done in the field of parallel I/O for scientific computing, specially for distributed memory machines. As shared memory systems gain popularity with the increasing number of cores in a node, implementing efficient parallel I/O for shared memory machines has become an important challenge. Currently, popular shared memory programming models like OpenMP do not provide a framework for implementing parallel I/O. This thesis provides a parallel I/O specification for shared memory architecture. In particular, focus has been laid on implementing parallel I/O for OpenMP. In the process, the characteristics of shared memory machines and the behavior of parallel file systems have been studied and an effort has been made to optimize parallel I/O. Also, this research provides insights into semantic analysis of data using the HDF5 technology suite.application/pdfengThe author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s).High performance computingHPCOpenMPParallelParallel I/OHdf5Computer science2013-12-02Thesisborn digital