A bit old but still interesting
Stop linking this, please! Any benchmark where Typescript and JavaScript are different is trash.
Why? Typescript transpiles into js but maybe the transpiler intruduces some overhead, isn’t it possible? I am not familiar with these languages, so this is an honest question.
It’s barely transpiled. There are a couple of features that involve actual code generation - enums and namespaces (which are almost never used), but the vast majority of it is just stripping the type annotations so the performance will be 100% identical.
It’s like having “Python” and “Python with type hints” as separate languages and claiming there is a big speed difference between them.
I was originally going to comment that differences in performance between JS and TS appear to be most significant in one challenge
ascii table about that, not screen reader friendly
___________________________________________________________________________________________________________________ |lang|_binary_trees___________|_fannkuch-redux_____________|_fasta_____________________|_normalized_________________| | JS | 312.14 : 21.349 : 916 | 413.90 : 33.663 : 26 | 64.84 : 5.098 : 30 | 4.45 : 6.52 : 4.59 | |_TS_|_315.10_:_21.686_:__915_|__6 898.48_:___516.541_:_26_|__82.72_:__6.909_:_____271_|____21.50_:___46.20_:__4.69_| |diff|___+.9%_:__+1.6%_:_+.1%_|_+15_66.7%_:_+14_34.4%_:_0%_|_+21.6%_:_+35.5%_:_+803.3%_|_+3_83.1%_:_+6_08.5_:_+8.1%_|however, trying to look to see the typescript code, wanting to translate that to type hinted python code, I’ve been unable to find typescript on CLBG, so I’m confused on how they got that data,
They used to have Typescript. Looks like they removed it at some point.
Very impressive study. I was surprised to learn that Ruby was categorized as functional but not object oriented. I thought that was their whole shstick.
Does anyone understand the Pearson coefficient part enough to explain it? I don’t really understand why they’re measuring correlation between memory, energy, and time in that way/ how you’d interpret it.
This study is what made me wanna go all-in on Rust. I still haven’t got around to for reasons, but I’m gradually picking up steam at rebooting personal projects. It’s only a matter of time.
I find this paper false/misleading. They just translated one algorithm in many languages, without using the language constructs or specificities to make the algorithm decent performant wise.
Also it doesn’t mean anything, as you aren’t just running your code. You are compiling/transpiling it, testing it, deploying it… and all those operations consume even more energy.
I’d argue that C/C++ projects use the most energy in term of testing due to the quantity of bugs it can present, and the amount of CPU time needed just to compile your 10-20k lines program. Just my 2 cents
