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the issue right now with Python support in WASM (at least for machine learning, the main driver of the language) is that Python is largely a wrapper language an

the issue right now with Python support in WASM (at least for machine learning, the main driver of the language) is that Python is largely a wrapper language and none the utilities that make it so powerful (numpy, PyTorch, JAX) work particularly well in wasm, since it's so limited performance-wise (no FMA, no GPU support). I'm excited for pairing wasm with WebGPU, which will likely unblock these projects from building support for the web/untrusted ecosystem. A useful project would be one that makes this integration really easy to build today and a flip of the switch to turn on in the future.

m00dy 4y ago
I have integrated pyodide + webgpu recently. (you can do matmul using webgpu's compute pipeline). The real problem is that browser tabs have 4gb max memory size. So, training neural networks on this stack is almost impossible. ( I don't even want to mention pyTorch's dependency hell).
- brrrrrm 4y ago
  My claim is that it’s not easy, not impossible. There’s little incentive to hack in JavaScript or maintain a Pyodide compatible build. The 4gb limit isn’t a technical limitation, just a standards thing (it could change easily).
- miohtama 4y ago
  WebAssembly Memory64 is coming https://webassembly.org/roadmap/ https://webassembly.org/roadmap/
mjw1007 4y ago
I've come across this notion that nowadays machine learning provides (in some sense) the biggest group of Python users a few times recently. What reason is there to suppose this is true? It seems surprising to me.
- claytonjy 4y ago
  It's really hard to do much ML in anything _except_ python. Virtually everyone improving the ML ecosystems of other language got their start in Python and are knowingly competing with Python (e.g. R, Julia). If you want to get started in ML today, python is the obvious easiest path forward. So, most ML users are python users. I don't know how that group compares to non-ML python users, but I have a feeling there isn't a flood of eager new Django devs the way there is Pytorch users. Most non-ML things you could do with python can be done similarly well in Go/Rust/Typescript, but there's no other option for most ML stuff.
  - mjw1007 4y ago
    I found a recentish (2021) survey at [1] which suggests that in 2021 ML was some way behind web development, sysadmin stuff, and data analysis among Python users (and didn't seem to be on the way up the list). [1] https://lp.jetbrains.com/python-developers-survey-2021/#GeneralPythonUsage https://lp.jetbrains.com/python-developers-survey-2021/#Gene...
    - claytonjy 4y ago
      Great source; looks like I've quite underestimated the python-web-dev crowd's size. I'm curious what the longer-term trends look like; not much change between consecutive years. Data analysis is basically a pre-requisite for ML, so the combined "data stuff" usage is quite a lot bigger than web dev usage!
    - aragilar 4y ago
      The obvious next question being, what's the difference between ML and data analysis from the perspective of the survey participants (is ML a strict subset)? Given the values don't add up to 100%, there's likely lots of overlap and so you could easily have web developers choosing Python for the ML ecosystem.
- _visgean 4y ago
  > What reason is there to suppose this is true? It seems surprising to me. One reason is its just super easy for input output operations. ML is all about data and getting the data to the right place is really easy in python compared to some other languages..
pjmlp 4y ago
Don't expect too much from WebGPU, its hardware target model for the MVP is how version 1.0 of modern GPU bindings used to be several years ago. In fact, in what concerns compute, it is hardly any better than GL ES compute shaders that Chrome refused to add to WebGL.

m00dy 4y ago

I have integrated pyodide + webgpu recently. (you can do matmul using webgpu's compute pipeline). The real problem is that browser tabs have 4gb max memory size. So, training neural networks on this stack is almost impossible. ( I don't even want to mention pyTorch's dependency hell).

brrrrrm 4y ago
My claim is that it’s not easy, not impossible. There’s little incentive to hack in JavaScript or maintain a Pyodide compatible build. The 4gb limit isn’t a technical limitation, just a standards thing (it could change easily).
miohtama 4y ago
WebAssembly Memory64 is coming https://webassembly.org/roadmap/ https://webassembly.org/roadmap/

mjw1007 4y ago

I've come across this notion that nowadays machine learning provides (in some sense) the biggest group of Python users a few times recently. What reason is there to suppose this is true? It seems surprising to me.

claytonjy 4y ago
It's really hard to do much ML in anything _except_ python. Virtually everyone improving the ML ecosystems of other language got their start in Python and are knowingly competing with Python (e.g. R, Julia). If you want to get started in ML today, python is the obvious easiest path forward. So, most ML users are python users. I don't know how that group compares to non-ML python users, but I have a feeling there isn't a flood of eager new Django devs the way there is Pytorch users. Most non-ML things you could do with python can be done similarly well in Go/Rust/Typescript, but there's no other option for most ML stuff.
- mjw1007 4y ago
  I found a recentish (2021) survey at [1] which suggests that in 2021 ML was some way behind web development, sysadmin stuff, and data analysis among Python users (and didn't seem to be on the way up the list). [1] https://lp.jetbrains.com/python-developers-survey-2021/#GeneralPythonUsage https://lp.jetbrains.com/python-developers-survey-2021/#Gene...
  - claytonjy 4y ago
    Great source; looks like I've quite underestimated the python-web-dev crowd's size. I'm curious what the longer-term trends look like; not much change between consecutive years. Data analysis is basically a pre-requisite for ML, so the combined "data stuff" usage is quite a lot bigger than web dev usage!
  - aragilar 4y ago
    The obvious next question being, what's the difference between ML and data analysis from the perspective of the survey participants (is ML a strict subset)? Given the values don't add up to 100%, there's likely lots of overlap and so you could easily have web developers choosing Python for the ML ecosystem.
_visgean 4y ago
> What reason is there to suppose this is true? It seems surprising to me. One reason is its just super easy for input output operations. ML is all about data and getting the data to the right place is really easy in python compared to some other languages..

pjmlp 4y ago

Don't expect too much from WebGPU, its hardware target model for the MVP is how version 1.0 of modern GPU bindings used to be several years ago. In fact, in what concerns compute, it is hardly any better than GL ES compute shaders that Chrome refused to add to WebGL.