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Toward Enabling Reproducibility for Data-Intensive Research using the
  Whole Tale Platform

Toward Enabling Reproducibility for Data-Intensive Research using the Whole Tale Platform

12 May 2020
Kyle Chard
N. Gaffney
M. Hategan
K. Kowalik
Bertram Ludäscher
T. McPhillips
J. Nabrzyski
V. Stodden
I. Taylor
Thomas Thelen
M. Turk
C. Willis
ArXiv (abs)PDFHTML

Papers citing "Toward Enabling Reproducibility for Data-Intensive Research using the Whole Tale Platform"

2 / 2 papers shown
Title
A Collective Knowledge workflow for collaborative research into
  multi-objective autotuning and machine learning techniques
A Collective Knowledge workflow for collaborative research into multi-objective autotuning and machine learning techniques
G. Fursin
Anton Lokhmotov
Dmitry Savenko
E. Upton
31
14
0
19 Jan 2018
On the State and Importance of Reproducible Experimental Research in
  Parallel Computing
On the State and Importance of Reproducible Experimental Research in Parallel Computing
S. Hunold
J. L. Traff
37
19
0
16 Aug 2013
1