I’ve been experimenting with OpenCL via pyopencl recently. They provide a nice interface for enumerating available devices and getting information about them, and then using them to run OpenCL code:
>>> import pyopencl as cl >>> platform = cl.get_platforms()[0] >>> platform.get_devices() [ <pyopencl.Device 'gfx1100' on 'AMD Accelerated Parallel Processing' at 0x56353125bd70>, <pyopencl.Device 'gfx1036' on 'AMD Accelerated Parallel Processing' at 0x5635312ec670> ] >>> There are two devices for me because I have one discrete 7900 XTX GPU as well as an integrated GPU on my 7950X CPU.
I recently upgraded to a 7900 XTX GPU. The upgrade itself went quite smoothly from both a hardware and software perspective. Games worked great out of the box with no driver or other configuration needed - as plug and play as it could possibly get.
However, I wanted to try out some machine learning on it. I’d been using TensorFlow.JS to train models using my GPU all in the browser, but that approach is limited compared to what’s possible when running it natively.
I recently upgraded to the 7900 XTX GPU which was a totally issue-free experience. Then today, I tried to install AMD ROCm so I could try out AMD’s TensorFlow fork that works with AMD GPUs.
I ran into a lot of issues with this that resulted in my computer not being able to boot for a while. I eventually figured it out, but it was quite a struggle.
It started after I downloaded and ran amdgpu-install - AMD’s tool for installing drivers and other software for use with their hardware.
Just today, I switched to the 7900 XTX GPU. I mostly just wanted an upgrade, but I also secretly hoped it would fix a lot of the weird GPU-related issues I’ve had over the past years.
The 5700 XT is a rather buggy GPU as far as I can tell - especially on Linux which is my only OS on my desktop. I’ve run into multiple bugs with drivers and other mysterious green-screen crashes:
TL;DR:
uPlot is a Spartan charting library that focuses intensely on minimalism and performance. It feels very much like a tool made for hackers, and it lacks many of the features and embellishments of fully-featured charting libraries.
The main downside is that it has quite terrible docs and sometimes has confusing APIs
I’m personally a big fan of its aesthetic and design goals, and I will probably be sticking with it as my primary charting library for the web for the forseeable future.