Abstract

Scientific workflows have been used almost universally across scientific domains, and have underpinned some of the most significant discoveries of the past several decades. Many of these workflows have high computational, storage, and/or communication demands, and thus must execute on a wide range of large-scale platforms, from large clouds to upcoming exascale high-performance computing (HPC) platforms. These executions must be managed using some software infrastructure. Due to the popularity of workflows, workflow management systems (WMSs) have been developed to provide abstractions for creating and executing workflows conveniently, efficiently, and portably. While these efforts are all worthwhile, there are now hundreds of independent WMSs, many of which are moribund. As a result, the WMS landscape is segmented and presents significant barriers to entry due to the hundreds of …

Date

January 1, 1970

Authors

Rafael Ferreira da Silva, Henri Casanova, Kyle Chard, Dan Laney, Dong Ahn, Shantenu Jha, Carole Goble, Lavanya Ramakrishnan, Luc Peterson, Bjoern Enders, Douglas Thain, Ilkay Altintas, Yadu Babuji, Rosa M Badia, Vivien Bonazzi, Taina Coleman, Michael Crusoe, Ewa Deelman, Frank Di Natale, Paolo Di Tommaso, Thomas Fahringer, Rosa Filgueira, Grigori Fursin, Alex Ganose, Bjorn Gruning, Daniel S Katz, Olga Kuchar, Ana Kupresanin, Bertram Ludascher, Ketan Maheshwari, Marta Mattoso, Kshitij Mehta, Todd Munson, Jonathan Ozik, Tom Peterka, Loic Pottier, Tim Randles, Stian Soiland-Reyes, Benjamin Tovar, Matteo Turilli, Thomas Uram, Karan Vahi, Michael Wilde, Matthew Wolf, Justin Wozniak

Journal

arXiv e-prints

Pages

arXiv: 2103.09181