131–140 of 269 posts
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That's how development under open source works. You can't please everyone.
There’s a big difference between developing something and announcing loudly that you have something cool; the developers have done the latter here.
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That's true, you never mentioned Python or alternatives in your README, I guess I got Mandela'ed from the comments in Hacker News, so my bad on that. People are naturally going to compare the timings and function you cite to what's available to the community right now, though, that's the only way we can picture its performance in real-life tasks. > Mojo or other languages, specifically because it generates hate Mojo…
Thanks, and I apologize if I got defensive, it is just that I put so much effort on being truthful, double-checking, putting disclaimers everywhere about every possible misinterpretation. Hell this is behind install instructions: > our code gen is still on its infancy, and is nowhere as mature as SOTA compilers like GCC and GHC Yet people still misinterpret. It is frustrating because I don't know what I could've done…
FWIW on HN people are inherently going to try to actually use your project and so if it's meant to be (long term) a faster way to run X people evaluate it against that implicit benchmark.
A lot of negativity in these threads. I say ~cudas~ kudos to the author for getting this far! The only similar project I'm aware of is Futhark, and that's haskell-y syntax - great for some people, but to the general class of C/C++/Python/Js/Java/etc. devs pretty arcane and hard to work with. My biggest complaint with this is, unlike Futhark, it only targets Cuda or multi-core. Futhark which can target OpenCL, Cuda, I…
Also NVidia has sponsored variants of Haskell, .NET, Java, Julia on CUDA, have a Python JIT and are collaborating with Mojo folks.
What kind of software would this language be good for? I assume it's not the kind of language you'd use for web servers exactly.
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> it is allocating 2 IC nodes for each numeric operation, while Python is not While that's true, Python would be using big integers (PyLongObject) for most of the computations, meaning every number gets allocated on the heap. If we use a Python implementation that would avoid this, like PyPy or Cython, the results change significantly: % cat sum.py def sum(depth, x): if depth == 0: return x else: fst = sum(depth-1, x…
The only claim I made is that it scales linearly with cores. Nothing else! I'm personally putting a LOT of effort to make our claims as accurate and truthful as possible, in every single place. Documentation, website, demos. I spent hours in meetings to make sure everything is correct. Yet, sometimes it feels that no matter how much effort I put, people will just find ways to misinterpret it. We published the real be…
from reply below:
> I apologize if I got defensive, it is just that I put so much effort on being truthful, double-checking, putting disclaimers everywhere about every possible misinterpretation.
I just want to say: don't stop. There will always be some people who don't notice or acknowledge the effort to be precise and truthful. But others will. For me, this attitude elevates the project to something I will be watching.
A lot of negativity in these threads. I say ~cudas~ kudos to the author for getting this far! The only similar project I'm aware of is Futhark, and that's haskell-y syntax - great for some people, but to the general class of C/C++/Python/Js/Java/etc. devs pretty arcane and hard to work with. My biggest complaint with this is, unlike Futhark, it only targets Cuda or multi-core. Futhark which can target OpenCL, Cuda, I…
Short example: https://github.com/m4rs-mt/ILGPU/blob/master/Samples/SimpleM...
Supports even advanced bits like inline PTX assembly: https://github.com/m4rs-mt/ILGPU/blob/master/Samples/InlineP...
Python-like + High-performance.
And, Different from Mojo, its Fully Open-Source.
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I think the issue is that there is the implicit claim that this is faster than some alternative. Otherwise what's the point? If you add some disclaimer like "Note: Bend is currently focused on correctness and scaling. On an absolute scale it may still be slower than single threaded Python. We plan to improve the absolute performance soon." then you won't see these comments. Also this defensive tone does not come off…
Right below install instructions, on Bend's README.md: > But keep in mind our code gen is still on its infancy, and is nowhere as mature as SOTA compilers like GCC and GHC. Second paragraph of Bend's GUIDE.md: > While cool, Bend is far from perfect. In absolute terms it is still not so fast. Compared to SOTA compilers like GCC or GHC, our code gen is still embarrassingly bad, and there is a lot to improve. That said,…
Yeah exactly. I read most of the readme and watched the demo, but I'm not interested in installing it so I missed this. I would recommend moving this to the first section in its own paragraph.
I understand you might not want to focus on this but it's important information and not a bad thing at all.