7 citations · 9 across the 2 of their papers we have counts for
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cs.PL2013★ 7 cited
How fast can we make interpreted Python?
Russell Power, Alex Rubinsteyn
Python is a popular dynamic language with a large part of its appeal coming from powerful libraries and extension modules. These augment the language and make it a productive envir…
cs.PL2013★ 2 cited
Locality Optimization for Data Parallel Programs
Eric Hielscher, Alex Rubinsteyn, Dennis Shasha
Productivity languages such as NumPy and Matlab make it much easier to implement data-intensive numerical algorithms. However, these languages can be intolerably slow for programs…