Okay, now do it by percent of processor (CPU/GPU/whatever) cycles.
Although, TBF, you can replace it all with C/C++. Or Rust, assume the optimisation has gotten good enough. It’s just that few people are both qualified for and interested in rewriting numerical linear algebra algorithms, and there’s no real reason to if the Fortran works.
I’ll never understand why my classmates prefer python to R.
Because R is incredibly clunky. I’ve worked with both and never got the hang of R.
import numpy as np temp = np.array([22, 21, 25, 23]) sd_temp = np.std(temp, ddof=1) print(sd_temp)Vs
temp <- c(22, 21, 25, 23) sd(temp)How in the world is R more clunky than python?
Edit: and I didn’t even mention how python likes to break unrelated software packages whenever I’m forced to use it.
I like my memes to come with a bibliography.
When you download R, youre downloading C++/C and Fortran
Everything is just silicon oxide gates being saturated and drained and turned on and off in various patterns very rapidly in a way that means something to us. That Fortran/C/C++/Assembly depends on that tiny two-MOSFET AND gate in the ALU to do the AND correctly every time.
Programming languages at the basic level are just an automated way of putting numbers into a calculator, processing them, and getting another number/status/flag back and doing something else with it based on the result.
meanwhile, me trying to get a feeling for how fast A GHz is by waving my arm as fast as I can:
Well I be damned. What does the Fortran do ?
Array operations in FORTRAN are much easier for the compiler heavily optimize than it is in c/c++ due to its array model and type system. You can achieve much of the same thing with modern compiler extensions, but it’s difficult and not as portable.
That’s interesting, thanks
Its just easy to write super-optimised code snippets in without having to break out into assembly.
What is the reason to avoid assembly? Is it prohibitively difficult?
Not only is it very difficult to write in assembly, the resulting code is not portable. Meaning that if you wrote it on x86 assembly it can’t run on ARM chips without emulation and that takes a significant hit on performance defeating the point
Yeah, it’s pretty difficult. Think of assembly as just one step above writing 1’s and 0’s, and you’re probably around how difficult it can be
I’ve delved into writing assembly only on the level of a student project. I really enjoyed it though. Obviously implementing a python math library would be far more complex but wouldn’t it be worth it for the possible performance gains?
I don’t think it would be anymore. Modern compilers are really really good at what they do, and often manually optimizing(writing assembly yourself) makes programs slower. So unless you are very good at assembly, I would just trust the compiler.
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But numpy is written in python and c/c++?
What does it say under the Languages section for that repo?
That I need to quit posting drunk because I can’t read obvious shit
Hope you’re feeling okay this morning Mr. Linksys, I love your username!
Numpy can use BLAS packages that are partly written in Fortran
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