Graham Markall

Apparently it's #MyTwitterAnniversary, so I'll use it as an opportunity to link to the Mastodon account I now use: @gmarkall" target="_blank" rel="nofollow noopener">mastodon.social/@gmarkall

Quick reminder that I'm mainly t[oo|wee]ting on Mastodon these days: @gmarkall" target="_blank" rel="nofollow noopener">mastodon.social/@gmarkall

Me on Mastodon: @gmarkall" target="_blank" rel="nofollow noopener">mastodon.social/@gmarkall I don't plan to disable this account, but I'm generally posting there these days.

Do you know about automatic differentiation and / or Enzyme? Could you help sketch out how AD support for @numba_jit could be implemented? Issue / thread: #issuecomment-1303072457" target="_blank" rel="nofollow noopener">github.com/numba/numba/is…

I've been on Mastodon a while but I got out of the habit of using it - this is my account that I'm starting to get active with again: @gmarkall" target="_blank" rel="nofollow noopener">mastodon.social/@gmarkall (is this usually written as @gmarkall@mastodon.social?). It has an old profile pic, still need to upload my current one.

@__mharrison__ Faster Python with @numba_jit

What do you Python for?

@9600 Uploading to pachube from my na-no-day

The Internet was much simpler when one the biggest questions of the day was how to pronounce Pachube.

@jonathandotcel @anthonypjshaw Yeah, the CPython Internals book is great for this, and I think there's a few blog posts on realpython.com that cover some of the same / similar material too

@gmarkall @anthonypjshaw Yeah, as a lang user it's pretty well abstracted but also reasonably intuitive as to what's going on C-side (in terms of e.g. "obviously this way will create tons of allocations" etc ). It's just really interesting to look at the inner workings and lower level concepts though!

I've been experimenting with using CUDA Unified Memory for the Python heap, towards a general goal of experimenting with a more unified CPU / GPU execution model within CPython, implemented as PyMemAllocatorEx instances. I have a few thoughts so far...

@apmasell If you optimise for size (-Os) I would imagine you have the best chance of that happening. I'm sure I've been aware of examples of that sort of thing but need to do a bit of digging.

@apmasell Maybe answering my own question, but it seems that constants in a constant pool have their own label in the asm source, so perhaps not part of the function. e.g. for 0x5f3759df in godbolt.org/z/vW3nYEcdT

@apmasell Years ago I recall trying to infer the size of functions, and I was working with elf files, working it out by looking for the following symbol. I maybe was an idiot and unaware of the size entry! How does it consider constant pools located near functions? Are they part of it?

@apmasell Does ELF have a way to do that if you haven't used something like -ffunction-sections?

@jonathandotcel @anthonypjshaw tutorial in the official docs suggests (docs.python.org/3/tutorial/ind…)... Though things might have been different if I'd been working in a different domain - I've not really used Python to implement a server app or anything like that, mainly compiler toolchain support / compiler work

@jonathandotcel @anthonypjshaw From a language user standpoint, I don't feel it's been that important to understand the internals of CPython - before I started working on Numba I think I was pretty happy just knowing the basics of the GIL (basically only one thread executing Python code) and what the...

@vellamike @anthonypjshaw Whoops, totally forgot to link to developer.nvidia.com/blog/unified-m… earlier - basically it's memory that can be accessed from CPU and GPU and migrated transparently between devices and host as required

@gmarkall @anthonypjshaw I would find this very interesting. I think in a blog post it would be great to provide some more background context? (e.g what is unified memory)

@anthonypjshaw 6. Finally, maybe this should have been a blog post with some code! Would that be interesting? What else should be answered / elaborated on if I write this up?

5. "CPython Internals" by @anthonypjshaw is a great intro / reference to CPython, saved me a lot of time, and got me up to speed quickly for this endeavour. Highly recommended if you want to poke about with this sort of stuff! (realpython.com/products/cpyth…)