Ralf Gommers, a core NumPy Maintainer, emphasized that long double support is 'extremely painful to maintain,' pointing to varied implementations across platforms, which lead to significant portability issues.
The complexities in building NumPy, especially on Windows, stem from the fact that MSVC uses a 64-bit long double, while Mingw-w64 defaults to 80 bits, complicating deployment and development.
Through developing numpy_quaddtype, Swayam Singh and Nathan Goldbaum aim to provide a cross-platform quadruple precision datatype to minimize errors caused by floating-point precision limitations in numerical simulations.
High precision in numerical computing addresses critical applications in fields like quantum physics and financial modeling, where even minor inaccuracies can lead to drastically different outcomes.
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