I see a lot of great numerical code in Julia. As a C++ developer, I don’t want to deal with a runtime or various parts of the language, but I imagine I could be more easily brought to the table if Julia code could be exported to a shared object file and linked against, or if it could compile to a direct binary.
I think Julia is the dark horse to eventually take over a wide swath of computing - possibly wider than Java or C++. As others have pointed out there's an effort to produce static Julia executables, and I think it's already possible to produce libraries. One interesting datapoint is that Julia's C FFI is faster than that of C++...
(For those interested, the order of the first few languages is: lua-jit, julia, c(!), c++, zig, nim, d in order of decreasing speed.)
It's extremely well thought out, concise, powerful, and readable. I think Julia's approach to types and multiple dispatch is a better alternative to traditional OO programming.
One thing the author didn't point out is that C++ (clang), Swift, Rust and Julia all use the LLVM infrastructure, resulting in extremely similar if not identical code generation. If datacenter efficiency truly becomes a priority, highly efficient languages like Julia, Rust and Swift will see increasing use for general purpose programming.
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I am a happy Julia user, but I can imagine if you had a use case where you wanted to compile a binary or shared library, Julia could be a pain.
C++ of course works fine for this but I imagine Swift would be less terrifying to use.
I think it will happen in the medium term future:
https://juliacomputing.com/blog/2016/02/09/static-julia.html https://github.com/JuliaComputing/static-julia https://github.com/JuliaComputing/llvm-cbe
I see a lot of great numerical code in Julia. As a C++ developer, I don’t want to deal with a runtime or various parts of the language, but I imagine I could be more easily brought to the table if Julia code could be exported to a shared object file and linked against, or if it could compile to a direct binary.
I think Julia is the dark horse to eventually take over a wide swath of computing - possibly wider than Java or C++. As others have pointed out there's an effort to produce static Julia executables, and I think it's already possible to produce libraries. One interesting datapoint is that Julia's C FFI is faster than that of C++...
https://github.com/dyu/ffi-overhead
(For those interested, the order of the first few languages is: lua-jit, julia, c(!), c++, zig, nim, d in order of decreasing speed.)
It's extremely well thought out, concise, powerful, and readable. I think Julia's approach to types and multiple dispatch is a better alternative to traditional OO programming.
One thing the author didn't point out is that C++ (clang), Swift, Rust and Julia all use the LLVM infrastructure, resulting in extremely similar if not identical code generation. If datacenter efficiency truly becomes a priority, highly efficient languages like Julia, Rust and Swift will see increasing use for general purpose programming.
Do you know how Julia gets such great ffi performance? Is it inlining, for instance?
It's a bit of a JIT party trick by emitting the target address directly rather than going through the PLT.