On Thu, 2014-11-06 at 02:41 +0000, Craig Dillabaugh via Digitalmars-d wrote: […] > Linear Algebra Library Cristi Cobzarenco David Simcha > based on SciD […]
Big Data (*) is the thing of the moment. Data science generally works in the relative small using Julia, R, and Python/SciPy/Matplotlib/Pandas. All the Java "Big Data" is fairly unsophisticated in comparison, in general anyway. I am not sure if there is any C++ stuff happening generally, there is a bit in the London quant scene, but R and Python dominate with Julia the up and coming outsider. If D really is as fast as C++ at execution and as fast as Python/R/Julia at development then it is not the language, it is the libraries that make it so. If D is to be a player then SciD need to get the same facilities as SciPy/Matplotlib/Pandas. NumPy on which the Python stuff is based is actually not as good as people make out, at least not at grunt performant parallel computation. Actually it is quite slow, I can get better performance using straight Python and Numba. On the other hand all the algorithms are already written on NumPy. So if SciD stopped being a Linear Algebra Library, and became a library of scientific (and statistical) algorithms with graphic visualization rendering, there is a small window of opportunity. On the downside, Julia, Python, R have a lot of backing. (*) Whatever that is. -- Russel. ============================================================================= Dr Russel Winder t: +44 20 7585 2200 voip: sip:[email protected] 41 Buckmaster Road m: +44 7770 465 077 xmpp: [email protected] London SW11 1EN, UK w: www.russel.org.uk skype: russel_winder
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