How an MIT research project became the Julia programming language
1–10 of 142 posts
Re: How an MIT research project became the Julia programming language
#2I really want to like Julia. It has a nice type system, a good ecosystem, reasonable syntax, and it’s far faster than Python. But there are several issues with its DX that prevent me from using it: the most severe of which being the complete lack of a cache for the JIT (or JIT like system), inducing multi second compile times for scripts that run in (I last tried Julia a few years ago; perhaps this has been improved since?)
Re: How an MIT research project became the Julia programming language
#3I really want to like Julia. It has a nice type system, a good ecosystem, reasonable syntax, and it’s far faster than Python. But there are several issues with its DX that prevent me from using it: the most severe of which being the complete lack of a cache for the JIT (or JIT like system), inducing multi second compile times for scripts that run in (I last tried Julia a few years ago; perhaps this has been improved…
a between session cache had been merged for 1.14 (release expected within 6-12 months).
Re: How an MIT research project became the Julia programming language
#4Julia uses 1-based indexing. It's competes with R and Matlab for the same set of users. Both R and Julia have their core functions written in C++. Absolutely nothing new.
From my experience, grad students use Julia when their PI thinks a new programming language will help differentiate their next NSF proposal among vast funding requests.
Re: How an MIT research project became the Julia programming language
#5Thought that it would be about Lisp....
Re: How an MIT research project became the Julia programming language
#6[deleted]
Re: How an MIT research project became the Julia programming language
#7Thought that it would be about Lisp....
It was about lisp ;)
Secret mode: ./julia —-lisp
Re: How an MIT research project became the Julia programming language
#8I really want to like Julia. It has a nice type system, a good ecosystem, reasonable syntax, and it’s far faster than Python. But there are several issues with its DX that prevent me from using it: the most severe of which being the complete lack of a cache for the JIT (or JIT like system), inducing multi second compile times for scripts that run in (I last tried Julia a few years ago; perhaps this has been improved…
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Re: How an MIT research project became the Julia programming language
#9Julia uses 1-based indexing. It's competes with R and Matlab for the same set of users. Both R and Julia have their core functions written in C++. Absolutely nothing new. From my experience, grad students use Julia when their PI thinks a new programming language will help differentiate their next NSF proposal among vast funding requests.
> Both R and Julia have their core functions written in C++. Absolutely nothing new.
imo this isn't really a good summary. Julia is one of the 3 languages to have done an exascale HPC run https://arxiv.org/pdf/2309.10292v1 (Fortran and C are the other 2). Some parts of the compiler are written in c++ (the llvm interface), but doing codegen with llvm is much more similar to C/Rust/Fortran than R/Matlab
Re: How an MIT research project became the Julia programming language
#10[flagged]