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by mm007emko
1132 days ago
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I use SBCL for research in nature-inspired algorithms. Not only you can use the same fast linear algebra libraries (BLAS, Lapack) as for instance NumPy does, recently they added support for SIMD instructions so you no longer have to call C or ASM code for vector (and matrix) computations if you have only a couple of small matrices and not on the "hot path" of your program. Most of the Common Lisp implementations used nowadays produce native code (or C or LLVM code which will be natively compiled). So you don't have to rewrite anything. Nowadays ML stuff is usually about matrix multiplications in its core so Python with NumPy (or a Cuda library) also delivers good enough performance. The native code is already there, just call it. You don't have to write it. |
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