wassenaar10

I was born in the late 90s so by the time I got involved in technology, my introduction to Unix and Unix-flavored systems was limited to Linux and MacOS. However, I've read about the history of Unix at Bell Labs, the BSD systems derived from research Unix, and the eventual commercial releases of Unix System V from AT&T themselves. I also see that HP-UX, AIX, and Solaris are apparently still maintained and get releases, which suggests that they are still being used in production in some places.

I'm curious if anyone here currently works (or has very recently worked) somewhere where proprietary Unix is still used for production. If so, can you tell me what they're used for and why those deployments haven't been moved to an appropriate Linux distribution?

Not suggesting Linux is necessarily better for all use cases, just wondering what keeps these small number of entities clinging to closed-source Unix with presumably pricey license costs.

I'd like to learn how to program for GPUs using either CUDA or OpenCL, and was wondering if anyone here could recommend a resource that could help me get started.

It would be awesome if there were a book or tutorial that walks you through environment configuration, and then shows you some examples of how to use the GPU to solve some real world, non graphics problems.

For the record, I'm not asking about graphics programming or OpenGL, I'm asking specifically about general purpose computing on GPUs.

An engineer (non-software) friend of mine asked me if range() was a function that had been added recently to Python, or if his professors just never showed it to him.

I told him range() has been there since the 90s and that his professors were just bad at Python. The thing is, I'm not actually sure about the first part. I know the history of some features, for example, I know that list-comprehensions were only added in Python 2 around 2000 and I know that map, reduce, and filter were added pretty early (like 1993) by programmers who were familiar with lisp. But I'm finding it really hard to find out when specific, arbitrary features were added to Python (or to other languages).

Google is no help because regardless of how I structure my query or tweak the search options, it just shows me endless SEO drivel sites that are only remotely related to what I searched. Anyone have a better way to find out stuff like this?

Pretty much what the title says.

AST (abstract syntax tree) interpreters are about the easiest form of language implementation to write, but they typically result in pretty slow performance due to the amount of memory they take up, the additional instructions involved in evaluating an AST, and the difficulty in making them cache-efficient. For this reason, it seems that most interpreted (or traditionally interpreted, e.g. "scripting languages") opt to use some combination of a bytecode interpreter or JIT-compilation for their most common implementations. Examples include Python , JavaScript, PHP, Lua, Perl, and so on.

I'm curious, however, what common (feel free to stretch the definition of "common") programming languages or implementations use an AST interpreter instead. From what I can tell it's not many - Matz's Ruby Interpreter is one of them, but I'm not very deep into the Ruby world and I don't know how common it is to use MRI vs another implementation. Besides that, I find it likely that many command line languages (bash, zsh, cmd.exe, powershell, etc.) and some Unix utils (like sed or awk, which are programming languages, albeit small ones) are implemented as simple AST interpreters since the most common usage patterns for these languages are short-running or IO-bound scripts and commands.

Curious to hear what everyone has to say and if any of my assumptions are incorrect.