Year: 2023
Type: conference-paper
Abstract: Julia is a dynamic language for scientific computing. For a dynamic language, Julia is surprisingly typeful. Types are used not only to structure data but also to guide dynamic dispatch – the main design tool in the language. No matter the dynamism, Julia is performant: flexibility is compiled away at the run time using a simple but smart type-specialization based optimization technique called type stability. Based on a model of a JIT mimicking Julia from previous works, we present the first algorithm to approximate type stability of Julia code. Implementation and evaluation of the algorithm is still a work in progress.
Author: Artem Pelenitsyn
Institution: Northeastern University
Language: English
Subfield: Software
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4387781683