An Ecosystem for Scientific Computing

By Brian E. Granger, Luis Obispo, John D. Hunter. 2011

Subfields: ML Systems & Hardware, Numerical Methods & Scientific Computing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In ML Systems & Hardware

1. Fernando Pérez
2. K. Jarrod Millman

In Numerical Methods & Scientific Computing

1. Thomas Günther
2. Fernando Pérez
3. K. Jarrod Millman
4. Shyue Ping Ong
5. Carsten Rücker
6. Florian M. Wagner
7. Christoph Weniger
8. G. Feiden

Citations in the corpus

• FireWorks: a dynamic workflow system designed for high‐throughput applications (2015, methodology): “FWS is implemented in the Python language, which is widely recognized as one of the major tools in modern scienti fi c computing, with extensive support for scienti fi c computing in almost every domain [7 – 9].”
• Developing Open-Source Scientific Practice * (2018, methodology): “In recent years, a number of web services have appeared that play the role of this central node; the most popular of them by far is GitHub, 27 but others such as BitBucket 28 and Gito-rious 29 play similar roles.”
• pyGIMLi: An open-source library for modelling and inversion in geophysics (2017, background): “…nature, which therefore makes it widely used in the (geo)scienti fi c community (e.g., Guyer et al., 2009; Logg and Wells, 2010; P (cid:1) erez et al., 2011; Wellmann et al., 2012; Uieda et al., 2013; Cockett et al., 2015; Weigand and Kemna, 2016; Hector and Hinderer, 2016; Schaa et…”