Energy-efficient approximate computation in Topaz
Thesis: S.M. in Computer Science and Engineering, Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2015
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| Online Access: | http://hdl.handle.net/1721.1/97329 |
| _version_ | 1811071163801010176 |
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| author | Achour, Sara |
| author2 | Martin C. Rinard. |
| author_facet | Martin C. Rinard. Achour, Sara |
| author_sort | Achour, Sara |
| collection | MIT |
| description | Thesis: S.M. in Computer Science and Engineering, Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015. |
| first_indexed | 2024-09-23T08:47:01Z |
| format | Thesis |
| id | mit-1721.1/97329 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T08:47:01Z |
| publishDate | 2015 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/973292019-04-10T07:31:05Z Energy-efficient approximate computation in Topaz Achour, Sara Martin C. Rinard. 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: S.M. in Computer Science and Engineering, Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015. Cataloged from PDF version of thesis. Includes bibliographical references (pages 69-73). The increasing prominence of energy consumption as a first-order concern in contemporary computing systems has motivated the design of energy-efficient approximate computing platforms. These computing platforms feature energy-efficient computing mechanisms such as components that may occasionally produce incorrect results. We present Topaz, a new task-based language for computations that execute on approximate computing platforms that may occasionally produce arbitrarily inaccurate results. The Topaz implementation maps approximate tasks onto the approximate machine and integrates the approximate results into the main computation, deploying a novel outlier detection and reliable re-execution mechanism to prevent unacceptably inaccurate results from corrupting the overall computation. Because Topaz can work effectively with a very broad range of approximate hardware designs, it provides hardware developers with substantial freedom in the designs that they produce. In particular, Topaz does not impose the need for any specific restrictive reliability or accuracy guarantees. Experimental results from our set of benchmark applications demonstrate the effectiveness of Topaz in vastly improving the quality of the generated output while only incurring 0.2% to 3% energy overheard. by Sara Achour. S.M. in Computer Science and Engineering 2015-06-10T19:10:14Z 2015-06-10T19:10:14Z 2015 2015 Thesis http://hdl.handle.net/1721.1/97329 910344373 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 73 pages application/pdf Massachusetts Institute of Technology |
| spellingShingle | Electrical Engineering and Computer Science. Achour, Sara Energy-efficient approximate computation in Topaz |
| title | Energy-efficient approximate computation in Topaz |
| title_full | Energy-efficient approximate computation in Topaz |
| title_fullStr | Energy-efficient approximate computation in Topaz |
| title_full_unstemmed | Energy-efficient approximate computation in Topaz |
| title_short | Energy-efficient approximate computation in Topaz |
| title_sort | energy efficient approximate computation in topaz |
| topic | Electrical Engineering and Computer Science. |
| url | http://hdl.handle.net/1721.1/97329 |
| work_keys_str_mv | AT achoursara energyefficientapproximatecomputationintopaz |