Comments (2)
twiecki
commented on July 19, 2024
I think this is definitely worth considering as writing your own Python-to-C++ compiler engine is an arduous task. numba also has GPU support.
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joschu
commented on July 19, 2024
Numba is a really excellent project, but I don't think it's the right fit here, since CGT's native backend uses some non-trivial C++ functionality, so it's more straightforward to implement the numerical operations in C++. That said, it's worth keeping numba in mind. The numba project also has some functionality for convenient LLVM code generation, which might be useful at some point.
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Related Issues (20)
- Product of diagonal elements may be `nan` HOT 1
- cgt.stack only supports stacking scalars HOT 1
- Error on tutorial
- Bug in graph simplification HOT 2
- OSX: Build fails with OpenBLAS dependency HOT 1
- Questions about Installation : cmake and windows HOT 1
- Memory consumption of native backend on Linux
- Random number generation and graph simplification HOT 2
- Negative reshaping check not enforced sometimes HOT 1
- Parameter indexing leads to an assertion error in module definition HOT 1
- Issues with shared scalar HOT 2
- Random number generation and modules (and simplification again)
- CIFAR Demo Error when using GPU
- Installation with anaconda
- Support for square root operation on Node HOT 2
- Simple operation breaks CGT
- Berkely BidMach and CGT
- How to build with python 3?
- Any reference to read? HOT 1
- Links in read-me are dead
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