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I don't know anything about common lisp, this seems to be a problem where Julia would shine marvelously. Given that most Julia users tend to be excellent mathem

by chaxor 4y ago

I don't know anything about common lisp, this seems to be a problem where Julia would shine marvelously. Given that most Julia users tend to be excellent mathematicians and physicists, I would imagine any advances or performance improvements in these types of calculations from the literature could be developed in Julia in a faction of the time that Fortran or C would take. In this case (numerics), the performance of Julia actually would probably be just as good as Fortran (or potentially faster due to being able to implement new ideas where performance enhancements quickly).

reikonomusha 4y ago
Julia indeed has great support for built-in linear algebra. They do lean on LAPACK (like just about any sane person/group would), but also re-implemented a lot of basic/common stuff natively in Julia. [1] > In addition to (and as part of) its support for multi-dimensional arrays, Julia provides native implementations of many common and useful linear algebra operations which can be loaded with using LinearAlgebra. > [...] > Linear algebra functions in Julia are largely implemented by calling functions from LAPACK. While the performance of numerical code in Common Lisp is quite excellent due to very good support for fast floating point math (especially with SBCL's recent addition of SB-SIMD [2]), the library support isn't quite there like it is for Julia or Python. That's slowly changing, with MAGICL, numcl, Numericals, and Lisp-Stat. A nice thing about Common Lisp compared to Julia or Python though is true AoT compilation without sacrificing a modicum of interactivity. [1] https://docs.julialang.org/en/v1/stdlib/LinearAlgebra/ https://docs.julialang.org/en/v1/stdlib/LinearAlgebra/ [2] http://www.sbcl.org/manual/index.html#sb_002dsimd http://www.sbcl.org/manual/index.html#sb_002dsimd
- adgjlsfhk1 4y ago
  I'm hopeful that within the next year, StaticCompiler.jl gets good enough to aot compile lapack type code. we're close, but there's still a lot of rough edges.

by chaxor 4y ago

reikonomusha 4y ago

Julia indeed has great support for built-in linear algebra. They do lean on LAPACK (like just about any sane person/group would), but also re-implemented a lot of basic/common stuff natively in Julia. [1] > In addition to (and as part of) its support for multi-dimensional arrays, Julia provides native implementations of many common and useful linear algebra operations which can be loaded with using LinearAlgebra. > [...] > Linear algebra functions in Julia are largely implemented by calling functions from LAPACK. While the performance of numerical code in Common Lisp is quite excellent due to very good support for fast floating point math (especially with SBCL's recent addition of SB-SIMD [2]), the library support isn't quite there like it is for Julia or Python. That's slowly changing, with MAGICL, numcl, Numericals, and Lisp-Stat. A nice thing about Common Lisp compared to Julia or Python though is true AoT compilation without sacrificing a modicum of interactivity. [1] https://docs.julialang.org/en/v1/stdlib/LinearAlgebra/ https://docs.julialang.org/en/v1/stdlib/LinearAlgebra/ [2] http://www.sbcl.org/manual/index.html#sb_002dsimd http://www.sbcl.org/manual/index.html#sb_002dsimd

adgjlsfhk1 4y ago
I'm hopeful that within the next year, StaticCompiler.jl gets good enough to aot compile lapack type code. we're close, but there's still a lot of rough edges.