Julia is a programming language for the scientific community that combines features of productivity languages, such as Python or MATLAB, with characteristics of performance-oriented languages, such as C++ or Fortran. Julia has many productivity features: dynamic typing, automatic memory management, rich type annotations, and multiple dispatch. At the same time, it lets programmers control memory layout and uses a specializing just-in-time compiler that eliminates some of the overhead of those features. This paper details these choices, and reflects on their implications for performance and usability.
Wed 7 NovDisplayed time zone: Guadalajara, Mexico City, Monterrey change
13:30 - 15:00
|AnyDSL: A Partial Evaluation Framework for Programming High-Performance Libraries|
Roland Leißa Saarland University, Germany, Klaas Boesche Saarland University, Sebastian Hack Saarland University, Germany, Arsène Pérard-Gayot Saarland University, Germany, Richard Membarth DFKI, Germany, Philipp Slusallek DFKI, Germany, André Müller Johannes Gutenberg University, Bertil Schmidt Johannes Gutenberg University
|Julia: Dynamism and Performance Reconciled by Design|
|GraphIt - A High-Performance Graph DSL|
|One Tool, Many Languages: Language-Parametric Transformation with Incremental Parametric Syntax|