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Fix sentence on interoperability #340

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Fix sentence on interoperability #340

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2 changes: 1 addition & 1 deletion paper/paper.md
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Expand Up @@ -74,7 +74,7 @@ The solvers rely heavily on iterative linear algebra methods from `Krylov.jl` [@
Julia's JIT compiler is attractive for the design of efficient scientific computing software, and, in particular, mathematical optimization [@lubin2015computing], and has become a natural choice for developing new solvers.

While several options exist to solve \eqref{eq:nlp} in Julia, many rely on wrappers to solvers implemented in low-level compiled languages.
For example, if \eqref{eq:nlp} is modeled using JuMP [@jump], it can be passed to solvers like IPOPT [@wachter2006implementation] or Artelys Knitro [@byrd2006k] via Julia’s native C++ and Fortran interoperability.
For example, if \eqref{eq:nlp} is modeled using JuMP [@jump], it can be passed to solvers like IPOPT [@wachter2006implementation] or Artelys Knitro [@byrd2006k] via Julia’s native C and Fortran interoperability.
However, these interfaces often lack flexibility with respect to data types and numerical precision.
In contrast, solvers written in pure Julia can operate seamlessly with a variety of arithmetic types or even GPU array types.
This capability is increasingly important as extended-precision arithmetic becomes more accessible through packages such as GNU MPFR, shipped with Julia.
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