A Grain Of Salt
Somehow, I stumbled upon an academic paper that compares programming language performance in the context of computing the results for a well-known, computationally dense, macro-economics problem: “the stochastic neoclassical growth model“. Since the results hoist C++ on top of the other languages, I felt the need to publish the researchers’ findings in this blog post :). As with all benchmarks, take it with a grain of salt because… context is everything.
Qualitative Findings
Quantitative Findings
The irony of this post is that I’m a big fan of Nassim Taleb, whose lofty goal is to destroy the economics profession as we know it. He thinks all the fancy, schmancy mathematical models and metrics used by economists (including famous Nobel laureates) to predict the future are predicated on voodoo science. They cause more harm than good by grossly misrepresenting and underestimating the role of risk in their assumptions and derived equations.
Author used VS 2010? Newer version got quite upgraded optimizations beside other things like most of C++11. (In contrast to GCC 4.8.2) Also it looks like old version of CPython.
Reblogged this on Bit of Code and commented:
Looks like it time to start using Numba!
Thanks for the reblog. Lemme guess – you’re a Python fan 🙂
Fan of J. Python by day.
I was a Python zealot then I over the course of a year I came to appreciate PHP’s strengths and see Pyhthon’s weaknesses. My current zeal is for languages that do not think real or integer numbers have a limit to their bits. Which has put me off Numpy and Scipy but I believe it is retrofittable because of the underlying language or because I know C/C++ and can write the replacement logic myself if it comes down to it. IAnd since you asked I’m currently a fan of J of jsoftware.com. I am still struggling to memorize the verbs and adverb combinations but I managed to solve the first 17 projecteuler.net challenges in J after doing them in Python anyway.