Extending the capabilities of Tiramisu
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.
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| Other Authors: | |
| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2018
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| Online Access: | http://hdl.handle.net/1721.1/119545 |
| _version_ | 1811074292148862976 |
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| author | Ben Romdhane, Malek |
| author2 | Saman P. Amarasinghe. |
| author_facet | Saman P. Amarasinghe. Ben Romdhane, Malek |
| author_sort | Ben Romdhane, Malek |
| collection | MIT |
| description | Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018. |
| first_indexed | 2024-09-23T09:46:45Z |
| format | Thesis |
| id | mit-1721.1/119545 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T09:46:45Z |
| publishDate | 2018 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1195452019-04-11T11:30:47Z Extending the capabilities of Tiramisu Ben Romdhane, Malek Saman P. Amarasinghe. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018. This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. Cataloged from student-submitted PDF version of thesis. Includes bibliographical references (pages 69-71). High performance computing requires not only writing highly efficient code, but also targeting multiple architectures (e.g. CPU, GPU, MPI). However, not only does bundling algorithm and optimization often obfuscate the code, but different architectures require different optimizations and programming tools. Tiramisu [3], an optimization framework, tries to solve this issue by separating algorithm, optimizations, and architecture details, and by targeting multiple architectures in a unified syntax. In this work, we highlight the implementation of a Julia interpreter that compiles a subset of the language to Tiramisu. We show that by adding simple Tiramisu optimization commands to Julia code, we can achieve up to 14x speedup. We also present an implementation of a CUDA backend for Tiramisu in order to target GPUs. We showcase a flexible Tiramisu CUDA API, as well as how common GPU usage patterns can be expressed in Tiramisu. We demonstrate that Tiramisu matches or outperforms the performance of the Halide GPU backend. by Malek Ben Romdhane. M. Eng. 2018-12-11T20:39:33Z 2018-12-11T20:39:33Z 2018 2018 Thesis http://hdl.handle.net/1721.1/119545 1076272808 eng MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582 71 pages application/pdf Massachusetts Institute of Technology |
| spellingShingle | Electrical Engineering and Computer Science. Ben Romdhane, Malek Extending the capabilities of Tiramisu |
| title | Extending the capabilities of Tiramisu |
| title_full | Extending the capabilities of Tiramisu |
| title_fullStr | Extending the capabilities of Tiramisu |
| title_full_unstemmed | Extending the capabilities of Tiramisu |
| title_short | Extending the capabilities of Tiramisu |
| title_sort | extending the capabilities of tiramisu |
| topic | Electrical Engineering and Computer Science. |
| url | http://hdl.handle.net/1721.1/119545 |
| work_keys_str_mv | AT benromdhanemalek extendingthecapabilitiesoftiramisu |