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APL at Julia's Speed | Shashi Gowda | JuliaCon 2016

The Julia Programming Language

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Intermediate. Assumes working knowledge.

3.4K views10 years ago1 recommendation

Programming languagesSystems programmingCompilers and interpretersPerformance and optimizationLanguage design and type systems

Shashi Gowda presents an implementation of APL in Julia that translates APL code into Julia data structures and JIT-compiles it to machine code.

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1 person recommends this

What people say. Recommended as a neat demonstration of Julia's extensibility and its capability to act as a high-level compiler target.

newenon Hacker News • Recommends

On “Compiling a Subset of APL into a Typed Intermediate Language (2014) [pdf]”

Reminds me of the APL interpreter in Julia ( link to this video ). The APL code gets translated to Julia data structures, which is then mapped to Julia code, which is then compiled to machine code via Julia's JIT. I thought it was a pretty neat way to run APL.
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vanderZwanon Hacker News • Mentions

On “Rust: The New LLVM”

Once static compilation gets off the ground, I wonder if Julia isn't an easier target for "high level LLVM". The whole language is built to be extensible, and people are already using it in comparable ways. APL implementation: link to this video As a code generator for the Go assembler: link
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ChrisRackauckason Hacker News • Mentions

On “APL deserves its renaissance too”

In fact, it can get extremely close: link to this video And since you can define your own operators, you could just go all of the way.
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improbable22on Hacker News • Mentions

On “APL – A Glimpse of Heaven (2006)”

I just found that there's a Julia package for at least some APL syntax, perhaps an easy way to play. 3 is a fork updated for v1.0: 1 link to this video 2 link 3 link
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u/GwanTheSwansin r/ProgrammingLanguages • Mentions

On “Seeking Ideas on Multi-Methods”

https://juliapackages.com/p/apl link to this video Julia intentionally has strong support for working with numeric arrays common in scientific computing... So it too pretty inevitably ends up with *some* commonality with classical APL/APL-like array languages. But so does matlab. And somewhat python+numpy. And somewhat F90/post-F90 fortran. Really the APL influence in the Julia case may largely be indirect through later matlab/octave, numpy and fortran, but e.g. fortran 90 was itself basically explicitly influenced by APL. It's enough that Julia is usually placed in the wider Array Programnming camp along with matlab etc even if it's not quite a linear descendant of an APL. Though of course all…
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