You can do extreme performance coding for Java, Javascript, R, Python, Haskell or the language of your choice as long as the number-crunching is done by calling low-level heavily optimized code. For example, PyCUDA:
And this is where I get told by data scientists that they don't wish to support such code. And IMO that's fine for piddling around and experimentation. But for production, on thousands to hundreds of thousands of servers, running 24/7, at companies with billions and billions of dollars in the bank, that's leaving way too many transistors and electrons on the table for me to stomach. In contrast, here's what you can achieve when you do pay attention to these things:
http://mathema.tician.de/software/pycuda/
And this is where I get told by data scientists that they don't wish to support such code. And IMO that's fine for piddling around and experimentation. But for production, on thousands to hundreds of thousands of servers, running 24/7, at companies with billions and billions of dollars in the bank, that's leaving way too many transistors and electrons on the table for me to stomach. In contrast, here's what you can achieve when you do pay attention to these things:
http://istc-bigdata.org/index.php/mapd-a-way-to-map-big-data...