Within 5 to 7 years, it’ll be an under $500 part, and no longer just for high-performance computing. 32 cores will be half that in price.
What computer language will be using to take advantage of that?
What computer language will be using to take advantage of that?
If you want low level you can use c, c++ which are both dangerous, rust, zig (I just did some multithreaded stuff in zig and it's fantastically easy).
could you share a little more about your experience here?
Like does zig have its own parallelism/threading in its standard library or do you have to link to a c library like pthreads?
1) A bit about what I'm doing with zig. I am working on an FFI interface between elixir and zig, with the intent to let you write zig code inline in elixir and have it work correctly (it does). https://github.com/ityonemo/zigler/. Arguably with zigler it's currently easier to FFI a C library than it is with C (I'm planning on making it even more easy; see example in readme).
2) The specific not-in-master-branch feature I'm working on now is running your zig code in a branched-off thread. Fun fact about the erlang VM: if you run native code it can cause the scheduler to get out of whack if the code runs too long. You can run it in a "dirty FFI" but your system restricts how many of these you can run at any given time. A better choice is to spawn a new OS thread, but that requires a lot of boilerplate to do and it's probably easy to get wrong. Making it also be a comprehensive part of erlang's monitoring and resource safety system is also challenging, and so there's a lot to do to keep it in line with Zigler's philosophy of making correctness simple.
3) Zig does have its own, opinionated way of doing concurrency. I honestly find it to be a bit confusing, but it's new (as of 6 months) and is not well documented. I believe the design constraints of this are guided by "not having red/blue functions", "being able to write concurrent library code that is safe to run on nonthreaded/nonthreadable systems"
4) The native zig way of doing concurrency is incompatible with exporting to a C ABI (without a shim layer) so I prefer not to use it anyways.
5) Zig ships with std.thread. I believe it's in the stdlib and not the language because some systems will not support threading. But since I'm writing something that is intended to bind into the erlang VM (BEAM), it's probably on a system that supports threading. Also I believe that std.thread will seamlessly pick either pthreads or not-pthreads based on the build target, which makes cross-compiling easy.
6) So yes, figuring this all out is not easy (zig is young, docs are not mature), but once you figure out what you're supposed to do, the actual code itself is a breeze, this is the code that I use to pack information to connect the beam to linux thread and launch it: https://github.com/ityonemo/zigler/blob/async/lib/zigler/lon.... I really hope the docs come with guides that will make this easy in the near future.
I'm relearning c++ right now just because I am building a poker solver for a toy project.
You are right btw, if 32 core cpus become common because of a race to the bottom in prices I imagine there will be a massive increase in demand for programmers with the experience to program massively parallel systems.
edit: and rust :)
Python is not at all suitable today for parallelism. Which is one reason why languages like Go and Elixir are gaining so much traction.
https://www.python.org/dev/peps/pep-0554/
This just may be the way forward in the Python ecosystem
It's a band-aid. If you want to run Python code in parallel, without large overhead, then CPython is simply not your environment to do so, and Python is not a good choice overall in that kind of endeavour.
As a long time Python dev, including work on parallel applications, I have to agree. It's always annoying in Python, and entirely Un-Pythonic.
If you're using Python to invoke highly-optimised native-code, then your performance will be excellent (as shown by the various Python numerical libraries), but performance-sensitive code shouldn't run in the Python interpreter.
As others have said, Python also lacks true multithreading (its threads are capable of concurrency but not parallelism, on account of the GIL), but you do have the option of just running a bunch of Python processes in parallel. I imagine that's a workable solution at least some of the time, but I've never explored this, so I don't know how good the library support is.
Edit: Someone else mentioned 'mpi4py' which seems to be a Python library for multi-process work.
That being said, I like it, but I tend to use Python more. I wish I had more of a chance to use Rust in my daily life, but I don't use it at work =/
Not out of the ordinary to see a SQL Server query using 20+ cores for a query with a parallelized plan
That said, one of my units has a clock speed that doesn't match any of the retail models (I guess they didn't end up selling that model?), and another doesn't seem to work with threading (or whatever AMD calls it) enabled. But that's a small price to pay for the money saved.