SparseRT: Accelerating Unstructured Sparsity on GPUs for Deep Learning Inference

dc.contributor.author	Wang, Ziheng
dc.date.accessioned	2022-11-03T14:58:25Z
dc.date.available	2022-11-03T14:58:25Z
dc.date.issued	2020-09-30
dc.identifier.isbn	978-1-4503-8075-1
dc.identifier.uri	https://hdl.handle.net/1721.1/146100
dc.publisher	ACM\|Proceedings of the 2020 International Conference on Parallel Architectures and Compilation Techniques	en_US
dc.relation.isversionof	https://doi.org/10.1145/3410463.3414654	en_US
dc.rights	Creative Commons Attribution 4.0 International license	en_US
dc.rights.uri	https://creativecommons.org/licenses/by/4.0/	en_US
dc.source	ACM\|Proceedings of the 2020 International Conference on Parallel Architectures and Compilation Techniques	en_US
dc.title	SparseRT: Accelerating Unstructured Sparsity on GPUs for Deep Learning Inference	en_US
dc.type	Article	en_US
dc.identifier.citation	Wang, Ziheng. 2020. "SparseRT: Accelerating Unstructured Sparsity on GPUs for Deep Learning Inference."
dc.contributor.department	Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.identifier.mitlicense	PUBLISHER_CC
dc.eprint.version	Final published version	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	2022-11-02T18:10:10Z
dc.language.rfc3066	en
dc.rights.holder	The author(s)
dspace.date.submission	2022-11-02T18:10:11Z
mit.license	PUBLISHER_CC
mit.metadata.status	Authority Work and Publication Information Needed	en_US