Temporal Data Placement

Sindhu, Muhammad Umair Javed Ilam (2022) Temporal Data Placement. Masters thesis, Memorial University of Newfoundland.

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How can we provide data where it is required and when it is required to the execution units of parallel hardware? Program transformations have been a focus to improve the performance of parallel computing, whereas data optimizations like data placement, data layout transformation, data migration and data replications are overlooked especially in compiler domain. We are proposing a methodology, Temporal Data Placement, that will schedule and place data in both time and space. The use of our methodology will enhance the performance of parallel systems significantly, and it can also be automated.

Item Type: Thesis (Masters)
URI: http://research.library.mun.ca/id/eprint/15435
Item ID: 15435
Additional Information: Includes bibliographical references (pages 105-110).
Keywords: data placement optimization, compile-time data placement, polyhedral model, polyhedral optimization, implementation of Farkas Lemma, linear programming, integer programming, mixed integer, non-linear programming
Department(s): Engineering and Applied Science, Faculty of
Date: May 2022
Date Type: Submission
Digital Object Identifier (DOI): https://doi.org/10.48336/XPB2-TS97
Library of Congress Subject Heading: Linear programming; Integer programming; Nonlinear programming; Parallel processing (Electronic computers); Parallel programming (Computer science).

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