Ray Tracing in Nim
nim-lang.org
Ray Tracing in Nim
1–10 of 68 posts
Re: Ray Tracing in Nim
#2What I like about Nim is that you can always get C performance if you just spend a little time. You can always use a profiler you like (I use vTune) to get to the hot loops and fix them.
See my post here: https://forum.nim-lang.org/t/5363#33576
Re: Ray Tracing in Nim
#3This is pretty good. I was wondering about CUDA and it looks like Nim has support for writing CUDA kernels. Is there a repository of kernel implementations I can take a look at?
Re: Ray Tracing in Nim
#4Anyone have thoughts on nim vs rust for data centric (Scala like) applications
Re: Ray Tracing in Nim
#5Anyone have thoughts on nim vs rust for data centric (Scala like) applications
If they’re data centric, would you not be better off with vanilla python? If you have numpy do the heavy lifting, it’ll be as fast plus all the syntactic/ecosystem benefits
Re: Ray Tracing in Nim
#6Anyone have thoughts on nim vs rust for data centric (Scala like) applications
Apart from Python, you could look at Julia.
Re: Ray Tracing in Nim
#7Anyone have thoughts on nim vs rust for data centric (Scala like) applications
If they’re data centric, would you not be better off with vanilla python? If you have numpy do the heavy lifting, it’ll be as fast plus all the syntactic/ecosystem benefits
Yeah, I like nim but it isn't going to offer and advantage over python in this regard.
Re: Ray Tracing in Nim
#8I keep seeing Nim and it looks really productive and very interesting! Does anyone know how it compares to Zig?
Re: Ray Tracing in Nim
#9Anyone have thoughts on nim vs rust for data centric (Scala like) applications
I can't speak to data centric but I was looking at both Rust and Nim for a project recently. I love the syntax of Nim and it feels incredibly easy to write in. The power of the macro system is amazing.
But the Rust community is so much bigger, pretty much every question I had was answered after a quick Google search.
Re: Ray Tracing in Nim
#10Anyone have thoughts on nim vs rust for data centric (Scala like) applications
If they’re data centric, would you not be better off with vanilla python? If you have numpy do the heavy lifting, it’ll be as fast plus all the syntactic/ecosystem benefits
The main reasons I see for nim in scientific computing over python are:
(a) you need performance for applications outside of numpy / pandas & you want to avoid writing a C extension to do so (nim is also actually a good choice for python extensions via nimpy - if you are still using python as the main language of your project/system)
(a2) you want good concurrency (some would say python's async/await is good - but it feels too little too late to me) & you at least want the option of parallelism (like this article takes advantage of)
(b) you want / need the powerful macro system for dsls / custom (compile-type-checkable) language extensions.
There is a good future for nim in scientific computing (frankly, there is a good present) - but for it to be better, people need to be willing to forgo some of the ecosystem (when possible) and to help build that future.