Computing in Science & Engineering · 2010 · 245 citations · 7 references
ComputingComputer ScienceComputer SystemsAlgorithmsParallel ComputingScientific ComputingComputational ModelsDistributed ComputingDistributed Data ProcessingNumerical AnalysisApplication ServersData-intensive ComputingLarge-scale Data ProcessingWeb Servers
As the relationship between research and computing evolves, new tools are required to not only treat numerical problems, but also to solve various problems that involve large datasets in different formats, new algorithms, and computational systems such as databases and Internet servers. Python can help develop these computational research tools by providing a balance of clarity and flexibility without sacrificing performance.
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Matplotlib: A 2D Graphics Environment
John D. Hunter · Computing in Science & Engineering · 2007 · 39.6K citations
Python for Scientific Computing
Travis E. Oliphant · Computing in Science & Engineering · 2007 · 3.4K citations
The Landscape of Parallel Computing Research: A View from Berkeley
Krste Asanović, Ras Bodik, Bryan Catanzaro et al. · 2006 · 2K citations
Engineering, Computer Science, High-performance Computing +17