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Chris Lattner is leading the project, of course they're using the language he designed. Personally I think they substantially underestimated the difficulty of s

Chris Lattner is leading the project, of course they're using the language he designed. Personally I think they substantially underestimated the difficulty of setting up a full technical computing ecosystem in Swift relative to Julia. But, fair enough, if I'd designed Swift I'd probably be dogfooding it too. Some previous discussions that mention the swift-vs-Julia decision: [1] https://news.ycombinator.com/item?id=19714622 https://news.ycombinator.com/item?id=19714622 [2] https://news.ycombinator.com/item?id=19884273 https://news.ycombinator.com/item?id=19884273

taharvey 7y ago
Actually this started before Lattner. Richard Wei kicked this off with his DLVM thesis. Either way, Swift's functional design around a type system has some compiler implications towards solving larger problems that Julia probably will struggle with as it moves forward beyond the goal of just being a faster Python.
- byt143 7y ago
  Specifically what?
  - taharvey 7y ago
    Essentially Swift is in Lattner's words "Syntactic sugar for LLVM"... meaning it was designed from a compilers point of view to provide an ontology for code that a compiler can analyze, interpret, optimize, and enable deeper functionality. Swift backed that ontology with a functional type system that forms a set proofs of the relationships and meaning of your code. If you take a language like C++, the "atoms" of the code like a Float32, are just hard coded intrinsics in the compiler. As such, they have no ontological meaning in relationship to a Float16, an Int32, or an Array of Strings. In Swift, a float is built from a set of proofs as equatable, hashable, Numeric, FloatingPointNumber, and etc. As related to Julia or Python, a static language built around these proofs, enable compiler's to provide "co-pilot" development assistance, guarantees at runtime, code validation. Why is this important? With deeper knowledge, a compiler can optimize things in ways that weren't previously possible, extract graphs, and automate code execution in heterogeneous computing evironments.

taharvey 7y ago

Actually this started before Lattner. Richard Wei kicked this off with his DLVM thesis. Either way, Swift's functional design around a type system has some compiler implications towards solving larger problems that Julia probably will struggle with as it moves forward beyond the goal of just being a faster Python.

byt143 7y ago
Specifically what?
- taharvey 7y ago
  Essentially Swift is in Lattner's words "Syntactic sugar for LLVM"... meaning it was designed from a compilers point of view to provide an ontology for code that a compiler can analyze, interpret, optimize, and enable deeper functionality. Swift backed that ontology with a functional type system that forms a set proofs of the relationships and meaning of your code. If you take a language like C++, the "atoms" of the code like a Float32, are just hard coded intrinsics in the compiler. As such, they have no ontological meaning in relationship to a Float16, an Int32, or an Array of Strings. In Swift, a float is built from a set of proofs as equatable, hashable, Numeric, FloatingPointNumber, and etc. As related to Julia or Python, a static language built around these proofs, enable compiler's to provide "co-pilot" development assistance, guarantees at runtime, code validation. Why is this important? With deeper knowledge, a compiler can optimize things in ways that weren't previously possible, extract graphs, and automate code execution in heterogeneous computing evironments.