expresscpp VS iswasmfast

I bench-marked using Intel vTune.

for loop is interesting. It's why Tensorflow Core written in C++ instead Java.

I don't know any complex C++ program that employ their own GCs when C++ has RAII which is superior to GC.

Just give a try for C++11/14/17 and you will see which one is more maintainable and expressive.

Look at Chromium codebase. It's the most beautiful codebase I've ever been to.

I've done a lot of CRUD web apps in C++ using expresscpp [1] and I would say it's easy as ABC.

A lot of Java folks haven't tried C++11/14/17 (Modern C++).

C++ is Zen of OOP.

[1] https://github.com/expresscpp/expresscpp

At a glance, the bindings for wasm copy the data,

https://github.com/zandaqo/iswasmfast/blob/54bbb7b539c127185...

If the running code is short enough then that copy might easily make the wasm version much slower. That is indeed a known downside of wasm (calls to JS are somewhat slow, and copying of data even more so - wasm shines when you can avoid those things).

If it's not that, then a 10x difference suggests you are running into some kind of a VM bug or limitation.

WASM has its moments, as you can see in this[1] benchmark it outperforms JS and native addons on certain tasks.

Since the bottleneck with native addons is usually data copying/marshalling, and we have direct access to WebAssembly memory from the JavaScript side, using WebAssembly on this "shared" memory might become the best approach for computationally heavy tasks. I wrote about it a bit here[2].

[1] https://github.com/zandaqo/iswasmfast

A few years ago I did similar comparison but in context of Node.js and sans manual optimizations: https://github.com/zandaqo/iswasmfast

In my work, I have come to conclusion that it seldom pays off to go "native" when working with Node.js. More often than not, rewriting some computationally heavy code in C and sticking it as a native module yielded marginally better results when compared with properly optimized js code. Though, that doesn't negate other advantages of using said technologies: predictable performance from the start and re-using existing code base.