Parallel I/O in Low Latency Storage Systems
| dc.contributor.advisor | Subhlok, Jaspal | |
| dc.contributor.committeeMember | Gabriel, Edgar | |
| dc.contributor.committeeMember | Shah, Shishir Kirit | |
| dc.contributor.committeeMember | Wu, Panruo | |
| dc.contributor.committeeMember | Ostilla-Mónico, Rodolfo | |
| dc.creator | Feki, Raafat | |
| dc.creator.orcid | 0000-0002-3541-5738 | |
| dc.date.accessioned | 2023-01-18T02:07:20Z | |
| dc.date.available | 2023-01-18T02:07:20Z | |
| dc.date.created | May 2022 | |
| dc.date.issued | 2022-05-01 | |
| dc.date.updated | 2023-01-18T02:07:21Z | |
| dc.description.abstract | The high performance computing (HPC) systems has known a momentous evolution during the last two last decades. Embedding thousands of cores, with very powerful processing capabilities, today’s supercomputers can process a tremendous amount of data in a matter of seconds. However, the evolution of the storage systems has not kept pace with it, which has led to a huge gap between I/O performance and processing performance. Therefore, computer scientists had mainly focused on improving the I/O performance by providing software solutions e.g. collective I/O and asynchronous I/O, that constitute the foundation of parallel I/O. They proposed several algorithms and techniques in order to hide the I/O overhead and improve the overall performance of storage systems by targeting the bandwidth and the capacity. The Message Passing Interface (MPI) has been the most recognized parallel programming paradigm for large scale parallel applications. Starting from version 2 of the MPI specification, the standard has introduced an interface for parallel file I/O support, referred to as MPI-I/O. By extending the MPI concepts to file I/O operations, the programming model becomes more complete and offers more options for developers to exploit the performance benefits of parallel I/O. While reaching the new era of Exascale computing, multiple innovative technologies has risen to the surface opening the door toward a balanced HPC ecosystem that incorporates low latency storage systems. Nevertheless, this evolution has also posed new challenges regarding parallel I/O optimizations. Whereas hardware latency was the main source of I/O overhead, software latency was usually negligible. However, in low latency storage systems, the equation changes since the former would be reduced to the same level as the latter. Therefore, we aim in this dissertation at solving the new equation by providing multiple optimization techniques to the existing parallel I/O solutions within MPI I/O context. In particular, this dissertation targets the communication overhead of collective I/O operations, the computation phase of complex access patterns within independent I/O operations and the file locking overhead of the Lustre parallel file system. | |
| dc.description.department | Computer Science, Department of | |
| dc.format.digitalOrigin | born digital | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.citation | Portions of this document appear in: Feki, Raafat, and Edgar Gabriel. "On Overlapping Communication and File I/O in Collective Write Operation." In 2020 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), pp. 1-8. IEEE, 2020; and in: Feki, Raafat, and Edgar Gabriel. "Design and Evaluation of Multi-threaded Optimizations for Individual MPI I/O Operations." In 2022 30th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP), pp. 122-126. IEEE, 2022. | |
| dc.identifier.uri | https://hdl.handle.net/10657/13638 | |
| dc.language.iso | eng | |
| dc.rights | The 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. UH Libraries has secured permission to reproduce any and all previously published materials contained in the work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s). | |
| dc.subject | HPC | |
| dc.subject | Parallel I/O | |
| dc.subject | MPI | |
| dc.title | Parallel I/O in Low Latency Storage Systems | |
| dc.type.dcmi | Text | |
| dc.type.genre | Thesis | |
| thesis.degree.college | College of Natural Sciences and Mathematics | |
| thesis.degree.department | Computer Science, Department of | |
| thesis.degree.discipline | Computer Science | |
| thesis.degree.grantor | University of Houston | |
| thesis.degree.level | Doctoral | |
| thesis.degree.name | Doctor of Philosophy |
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