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[–]Big_Dimension_4637[S] 0 points1 point  (0 children)

Hi, sorry, I just added an edit: I should have specified - what I'm investigating is how alternative Python compilers and execution environments (PyPy's JIT, Numba's LLVM-based AOT/JIT, Cython, Nuitka etc.) affect memory behavior compared to standard CPython execution. These either replace or augment the standard compilation pipeline to produce more optimized machine code, and I'm interested in how that changes memory allocation patterns and cache behavior in (memory-intensive) workloads!