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Anant Agarwal. Duvall, Michelle, 1981- Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science 2005-09-26T20:11:14Z 2005-09-26T20:11:14Z 2004 2004 http://hdl.handle.net/1721.1/28389 56961474 Thesis (M. Eng. and S.B.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004. Includes bibliographical references (p. 101-103). Wire delays and communication time are forcing processors to become decentralized modules communicating through a fast, scalable interconnect. For scalability, every portion of the processor must be decentralized, including the memory system. Compilers that can take a sequential program as input and parallelize it (including the memory) across the new processors are necessary. Much research has gone towards the ensuing problem of optimal data layout in memory and instruction placement, but the problem is so large that some aspects have yet to be addressed. This thesis presents spatial software pipelining, a new mechanism for doing data layout and instruction placement for loops. Spatial software pipelining places instructions and memory to avoid communication cycles, decreases the dependencies of tiles on each other, allows the bodies of loops to be pipelined across tiles, allows branch conditions to be pipelined along with data, and reduces the execution time of loops across multiple iterations. This thesis additionally presents the algorithms used to effect spatial software pipelining. Results show that spatial software pipelining performs 2.14x better than traditional assignment and scheduling techniques for a sparse matrix benchmark, and that spatial software pipelining can improve the execution time of certain loops by over a factor of three. by Michelle Duvall. M.Eng. S.B. 103 p. 5290118 bytes 5302254 bytes application/pdf application/pdf en_US 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. Spatial software pipelining on distributed architectures for sparse matrix codes Thesis application/pdf Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="1fed3b53-1ca7-4fe7-a521-feb2dc6678d4"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>en_US</Language> <Title>Spatial software pipelining on distributed architectures for sparse matrix codes</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2004</PublicationDate> <Authors> <Author> <DisplayName>Duvall, Michelle, 1981-</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>Wire delays and communication time are forcing processors to become decentralized modules communicating through a fast, scalable interconnect. For scalability, every portion of the processor must be decentralized, including the memory system. Compilers that can take a sequential program as input and parallelize it (including the memory) across the new processors are necessary. Much research has gone towards the ensuing problem of optimal data layout in memory and instruction placement, but the problem is so large that some aspects have yet to be addressed. This thesis presents spatial software pipelining, a new mechanism for doing data layout and instruction placement for loops. Spatial software pipelining places instructions and memory to avoid communication cycles, decreases the dependencies of tiles on each other, allows the bodies of loops to be pipelined across tiles, allows branch conditions to be pipelined along with data, and reduces the execution time of loops across multiple iterations. This thesis additionally presents the algorithms used to effect spatial software pipelining. Results show that spatial software pipelining performs 2.14x better than traditional assignment and scheduling techniques for a sparse matrix benchmark, and that spatial software pipelining can improve the execution time of certain loops by over a factor of three.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>