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Title: Apollo

Abstract

Modern performance portability frameworks provide application developers with a flexible way to determine how to run application kernels, however, they provide no guidance as to the best configuration for a given kernel. Apollo provides a model-generation framework that, when integrated with the RAJA library, uses lightweight decision tree models to select the fastest execution configuration on a per-kernel basis

Authors:
 [1];  [1]
  1. LLNL
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
Contributing Org.:
Lawrence Livermore National Laboratory
OSTI Identifier:
1372460
Report Number(s):
Apollo; 005366MLTPL00
LLNL-CODE-733798
DOE Contract Number:
AC52-07NA27344
Resource Type:
Software
Software Revision:
00
Software Package Number:
005366
Software CPU:
MLTPL
Source Code Available:
Yes
Country of Publication:
United States

Citation Formats

Beckingsal, David, and Gamblin, Todd. Apollo. Computer software. Vers. 00. USDOE National Nuclear Security Administration (NNSA). 17 Apr. 2017. Web.
Beckingsal, David, & Gamblin, Todd. (2017, April 17). Apollo (Version 00) [Computer software].
Beckingsal, David, and Gamblin, Todd. Apollo. Computer software. Version 00. April 17, 2017.
@misc{osti_1372460,
title = {Apollo, Version 00},
author = {Beckingsal, David and Gamblin, Todd},
abstractNote = {Modern performance portability frameworks provide application developers with a flexible way to determine how to run application kernels, however, they provide no guidance as to the best configuration for a given kernel. Apollo provides a model-generation framework that, when integrated with the RAJA library, uses lightweight decision tree models to select the fastest execution configuration on a per-kernel basis},
doi = {},
year = {Mon Apr 17 00:00:00 EDT 2017},
month = {Mon Apr 17 00:00:00 EDT 2017},
note =
}

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