Type of Document Master's Thesis Author Attari, Sanya Author's Email Address firstname.lastname@example.org URN etd-12162010-111619 Title An Investigation of I/O Strategies for MPI Workloads Degree Master of Science Department Computer Science Advisory Committee
Advisor Name Title Butt, Ali R. A. Committee Chair Nazhandali, Leyla Committee Member Tatar, Deborah Gail Committee Member Keywords
Date of Defense 2010-12-02 Availability unrestricted AbstractDifferent techniques could be used for improving application performance in parallel systems. Studies have been shown that I/O communication delay is the main reason for different behavior of I/O intensive applications with specific requirements for performance optimization. So, using common strategies, generally defined and effective for computationally intensive applications may not have the same effect on performance improvement for these applications. Moreover, background system configuration effects on the behavior of the application and its performance. Growing use of parallel multi-core systems is an important factor in increasing performance and speeding up the applications. Since changing multi-core systems hardware is not an efficient method in satisfying different expectations of unique application, it is application developer's responsibility to design flexible and scalable code that is compatible with different environments. On the other hand, predicting application behavior and I/O requirements for I/O intensive applications with irregular communication patterns is a complicated and time-consuming task that pushes the problem to runtime impacts.
Addressing this issue, we provided an overview on different techniques used for solving this problem.
We have studied I/O bound parallel applications that use MPI as the communication method in order to define a general perspective to optimize cost performance ratio. Our designed experiments cover different setups for these applications in order to define various criteria that should be considered in design stage as well as runtime. Moreover, targeting one of the popular I/O intensive applications, we have discussed some possible solutions to speed it up on a multi-core system.
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