Y
HN Search
Hacker News Search
new
|
comments
|
top
|
jobs
certik
searching PlanetScale…
1.
▲
2.
▲
3.
▲
4.
▲
5.
▲
6.
▲
10 ms
·
61.
▲
by
certik
3y ago
Definitely let us know any feedback once you try it. You can open up an issue at lpython github.
62.
▲
by
certik
3y ago
Then it's an optimizing compiler for sure.
63.
▲
by
certik
3y ago
I would say LPython, Codon, Mojo and Taichi are structured similarly as compilers written in C++, see the links at the bottom of https://lpython.org/ . Internally they each parse the syntax to AST, then have some kind of an
64.
▲
by
certik
3y ago
> Looks interesting! Thank you for focusing on AoT compilation and not just JIT compilation. To be honest, I'm sick of JIT compilation. In theory it seems like the best of both worlds, but in practice it turns out to be the worst o
65.
▲
by
certik
3y ago
You are right, we should have made that clearer. If you look at all the 25 compilers that we list at the bottom of: https://lpython.org/ , some of them are supersets, some of them are subsets. Sometimes the distinction is bl
66.
▲
by
certik
3y ago
Yes, try `conda install -c conda-forge lpython`. It should work on Windows, but it's not as extensively tested as macOS and Linux. If it doesn't work, please report it, and we'll fix it. Once we get to beta, we will support W
67.
▲
by
certik
3y ago
It was the easiest for us to deliver a binary that works on Linux, macOS and Windows. Others can then use this binary as a reference to package LPython into other distributions. You can also install LPython from source, but it's harder
68.
▲
by
certik
3y ago
Mojo is a strict superset of Python, LPython is a strict subset of Python. We could target MLIR later, right now we are just targeting LLVM.
69.
▲
by
certik
3y ago
Yes, the Numba use case is a subset of LPython. We want to support what Numba does, that is, you decorate your function and JIT it. But in addition, we also want to compile to binaries (ahead of time) that have no CPython dependency, and su
70.
▲
by
certik
3y ago
Yes, LPython is a strict subset of Python, while Mojo is a strict superset of Python. Both are valid and consistent approaches with their pros and cons, I listed some of them here: https://fortran-lang.discourse.group/t/
71.
▲
by
certik
3y ago
Yes, we can compare with pythran too. We should really compare against all the other compilers, but it's a lot of work to compare meaningfully: we don't want to put up benchmarks unless we are really sure they are solid, and as ev
72.
▲
by
certik
3y ago
No, we had LFortran, so naturally we have LPython now as the second frontend. We chose "L" in LFortran to be unspecified, although let's just say I live in L os Alamos, and we use L LLVM.
73.
▲
by
certik
3y ago
> Nitpick: The "Documentation" button on the header links to LFortran, not LPython. Yes, I noticed too, thanks. We currently don't have a dedicated documentation for LPython and a lot of the LFortran documentation applies
74.
▲
by
certik
3y ago
Awesome, thank you. I knew about mypyc, but forgot. I just put it in: https://github.com/lcompilers/lpython.org-deploy/pull/37 So now we have 25 compilers there. Yes, the current syntax to call CPython is low
75.
▲
by
certik
3y ago
A compiler doesn't need to optimize. I think if it takes Python code, and translates it to something else, it's a compiler. An optimizing compiler is the one that will give you speedups.
76.
▲
by
certik
3y ago
Nuitka is a compiler. With list it at the bottom of https://lpython.org/ , together with the other 23 Python compilers, now 24. :)
77.
▲
by
certik
3y ago
Right we support (currently a subset) of NumPy (just `from numpy import ...`) and SymPy (`from sympy import ...`) and some parts of the Python standard library. We want to support PyTorch, CuPy and other such libraries in a similar way, at
78.
▲
by
certik
3y ago
> - presumably, since it is compiled, it does static checks on the code? How many statically-detectable bugs that are now purely triggered at runtime can be eliminated with LPython? Yes, it does static checks at compile time. The only th
79.
▲
by
certik
3y ago
We put this sentence there to drive the point home that LPython competes with C++, C and Fortran in terms of speed. The internals are shared with LFortran, and LFortran competes with all other Fortran compilers, that traditionally are often
80.
▲
by
certik
3y ago
Hi William, nice to hear from you. We mention Cython at our front page (at the bottom): https://lpython.org/ , together with the other 23 Python compilers that I know about (all of them are competitors, in a way). I am very
81.
▲
by
certik
3y ago
We are interested for outside use, but right now we just copy (and sync) the libasr directory with LPython/LFortran manually. All the commits thus go first into either one of the frontends. We decided on this approach as it is currentl
82.
▲
by
certik
3y ago
The author here. If you have any questions, let me know. If there is anybody here who wants to help parallelize this, let me know!
83.
▲
by
certik
3y ago
Thank you, we really appreciate it!
84.
▲
by
certik
3y ago
If you are not a Bing frontend, do you think it would be please possible to unblock our Fortran webpage at fortran-lang.org? See here for details: https://fortran-lang.discourse.group/t/fortran-lang-no-longe... Bing de
85.
▲
by
certik
3y ago
This is a very important effort: if SciPy accepts this modern Fortran codebase, then I think the tide for Fortran will change. My own focus is to compile all of SciPy with LFortran, we can already fully compile the Minpack package, here is
86.
▲
by
certik
4y ago
I don't have much GPU experience myself. As the sibling comment said, there are Fortran compilers that can offload to GPU, there is also Cuda Fortran. There is OpenMP offloading. I think LLVM can also target it somehow, and I would lik
87.
▲
by
certik
4y ago
It's here: https://github.com/certik/theoretical-physics/ , I was hoping more people would contribute to the effort, but so far I didn't manage to spark enough interest. It's open source, it's o
88.
▲
by
certik
4y ago
Excellent questions. One is import time and model loading time where PyTorch is very slow, and it gets much worse for the larger models, for the 1558M model PyTorch is 24s to start, while fastGPT is 1s, about 24x speedup. I am still studyin
89.
▲
by
certik
4y ago
Sorry about that. I was using some Hugo theme and I haven't checked on mobile. I should redo my webpage to be mobile friendly.
90.
▲
by
certik
4y ago
The author here. I am happy to answer any questions.
More ›