2026-09-19T05:56:35Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1006752026-06-06T00:55:13Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Saman Amarasinghe.
Epstein, Aaron, M. Eng. (Aaron B.). Massachusetts Institute of Technology
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2016-01-04T20:52:22Z
2016-01-04T20:52:22Z
2015
2015
http://hdl.handle.net/1721.1/100675
932128346
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015.
Cataloged from PDF version of thesis.
Includes bibliographical references (page 37).
Halide is a tool that makes writing efficient code easier to design, maintain, and operate. However, Halide is currently limited to building programs that run on one machine, which bounds both the size of the input and the speed of computation. My work involves adding distributed computation as an option for running Halide programs. Enabling distributed computation would allow Halide to be run at a much larger scale and solve larger problems like weather simulation and 3D rendering. This project has dealt with how Halide can analyze what data programs will need to share and how they can efficiently share it. Using my work, a programmer can easily divide their input into several small chunks and start an instance of their program to solve each chunk with synchronization and data sharing handled through Halide.
by Aaron Epstein.
M.Eng.
38 pages
eng
Massachusetts Institute of Technology
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
Electrical Engineering and Computer Science.
A distributed backend for Halide
Thesis
application/pdf
false
Publication
unknown
unknown
<Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="97ea27c4-ece7-46d8-88a4-af949ae3d71e">
<Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type>
<Language>eng</Language>
<Title>A distributed backend for Halide</Title>
<PublishedIn>
<Publication>
</Publication>
</PublishedIn>
<PublicationDate>2015</PublicationDate>
<Authors>
<Author>
<DisplayName>Epstein, Aaron, M. Eng. (Aaron B.). Massachusetts Institute of Technology</DisplayName>
<Affiliation>
<OrgUnit>
</OrgUnit>
</Affiliation>
</Author>
</Authors>
<Editors>
</Editors>
<Publishers>
<Publisher>
<DisplayName>Massachusetts Institute of Technology</DisplayName>
<OrgUnit />
</Publisher>
</Publishers>
<License>http://dspace.mit.edu/handle/1721.1/7582</License>
<Keyword>Electrical Engineering and Computer Science.</Keyword>
<Abstract>Halide is a tool that makes writing efficient code easier to design, maintain, and operate. However, Halide is currently limited to building programs that run on one machine, which bounds both the size of the input and the speed of computation. My work involves adding distributed computation as an option for running Halide programs. Enabling distributed computation would allow Halide to be run at a much larger scale and solve larger problems like weather simulation and 3D rendering. This project has dealt with how Halide can analyze what data programs will need to share and how they can efficiently share it. Using my work, a programmer can easily divide their input into several small chunks and start an instance of their program to solve each chunk with synchronization and data sharing handled through Halide.</Abstract>
<Access xmlns="http://purl.org/coar/access_right"
>
</Access>
</Publication>