Uncovering Performance Opportunities by Relaxing Program Semantics of GPGPU Kernels

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{Liou:2019:GPGPU,

• author = "Jhe-Yu Liou and Stephanie Forrest and Carole-Jean Wu",
• title = "Uncovering Performance Opportunities by Relaxing Program Semantics of {GPGPU} Kernels",
• booktitle = "12th Workshop on General Purpose Processing Using GPU (GPGPU 2019) @ ASPLOS 2019",
• year = "2019",
• editor = "Adwait Jog and Onur Kayiran and Ashutosh Pattnaik",
• address = "Providence, RI, USA",
• month = "13-17 " # apr,
• keywords = "genetic algorithms, genetic programming, genetic improvement, GPU, GEVO, LLVM-IR, GEVO-APPROX, MNIST, a9a, SVM, NVIDIA Tesla P1000 GPU",
• URL = "https://asplos-conference.org/2019/index.html@p=824.html",
• URL = "https://asplos-conference.org/2019/wp-content/uploads/2019/04/asplos19waci-liou-forrest-wu.pdf",
• size = "2 pages",
• notes = "See also \cite{Liou:2019:GI}, \cite{Liou:2020:ACMtaco}

  https://insight-archlab.github.io/gpgpu.html",

}

Genetic Programming entries for Jhe-Yu Liou Stephanie Forrest Carole-Jean Wu

Citations