dc.contributor.author | Baghdadi, Mohamed Riyadh | |
dc.contributor.author | Ray, Jessica Morgan | |
dc.contributor.author | Romdhane, Malek Ben | |
dc.contributor.author | Del Sozzo, Emanuele | |
dc.contributor.author | Akkas, Abdurrahman | |
dc.contributor.author | Zhang, Yunming | |
dc.contributor.author | Suriana, Patricia | |
dc.contributor.author | Kamil, Shoaib | |
dc.contributor.author | Amarasinghe, Saman P | |
dc.date.accessioned | 2020-11-30T22:48:45Z | |
dc.date.available | 2020-11-30T22:48:45Z | |
dc.date.issued | 2019-03 | |
dc.date.submitted | 2019-02 | |
dc.identifier.isbn | 9781728114361 | |
dc.identifier.uri | https://hdl.handle.net/1721.1/128700 | |
dc.description.abstract | This paper introduces Tiramisu, a polyhedral framework designed to generate high performance code for multiple platforms including multicores, GPUs, and distributed machines. Tiramisu introduces a scheduling language with novel commands to explicitly manage the complexities that arise when targeting these systems. The framework is designed for the areas of image processing, stencils, linear algebra and deep learning. Tiramisu has two main features: it relies on a flexible representation based on the polyhedral model and it has a rich scheduling language allowing fine-grained control of optimizations. Tiramisu uses a four-level intermediate representation that allows full separation between the algorithms, loop transformations, data layouts, and communication. This separation simplifies targeting multiple hardware architectures with the same algorithm. We evaluate Tiramisu by writing a set of image processing, deep learning, and linear algebra benchmarks and compare them with state-of-the-art compilers and hand-tuned libraries. We show that Tiramisu matches or outperforms existing compilers and libraries on different hardware architectures, including multicore CPUs, GPUs, and distributed machines. | en_US |
dc.language.iso | en | |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1109/cgo.2019.8661197 | en_US |
dc.rights | Creative Commons Attribution-Noncommercial-Share Alike | en_US |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/4.0/ | en_US |
dc.source | MIT web domain | en_US |
dc.title | Tiramisu: A Polyhedral Compiler for Expressing Fast and Portable Code | en_US |
dc.type | Article | en_US |
dc.identifier.citation | Baghdadi, Riyadh et al. "Tiramisu: A Polyhedral Compiler for Expressing Fast and Portable Code." 2019 IEEE/ACM International Symposium on Code Generation and Optimization, February 2019, Washington, DC, USA, Institute of Electrical and Electronics Engineers, March 2019. © 2019 IEEE | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory | en_US |
dc.relation.journal | 2019 IEEE/ACM International Symposium on Code Generation and Optimization (CGO) | en_US |
dc.eprint.version | Author's final manuscript | en_US |
dc.type.uri | http://purl.org/eprint/type/ConferencePaper | en_US |
eprint.status | http://purl.org/eprint/status/NonPeerReviewed | en_US |
dc.date.updated | 2020-11-24T17:13:27Z | |
dspace.orderedauthors | Baghdadi, R; Ray, J; Romdhane, MB; Sozzo, ED; Akkas, A; Zhang, Y; Suriana, P; Kamil, S; Amarasinghe, S | en_US |
dspace.date.submission | 2020-11-24T17:13:40Z | |
mit.license | OPEN_ACCESS_POLICY | |
mit.metadata.status | Complete | |