{ "authors": [ { "name": "8b8a92b1383df1e4" }, { "name": "00f063a6468f92f9" }, { "name": "aba5db34221991c7" }, { "name": "0728a400aa1c86fe" }, { "name": "07b8b4bd98945c99" }, { "name": "f32f5b6d20249eb9" }, { "name": "7977d39d0f90f2ce" }, { "name": "90962ba7d347f2fc" }, { "name": "a3ed754096bb8d9b" } ], "bib_ref": "cm:29db2248aba45e59:0a69fbd474cdd888", "local_bib": "doc.bib", "local_doc": "doc.pdf", "place": "", "publish_iso_date": "2020-10-20", "reproducible": "yes", "title": "On the Anatomy of Predictive Models for Accelerating GPU Convolution Kernels and Beyond", "type": { "name": "journal", "peer_reviewed": "yes", "scope": "international" }, "when": "October 2020", "where": "Accepted for the ACM Transactions on Architecture and Code Optimization (TACO)" }
{}