English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Technical computing is a challenging application area for programminglanguages to address. This is evinced by the unusually large number ofspecialized languages in the area (e.g. MATLAB, R), and the complexity ofcommon software stacks, often involving multiple languages and custom codegenerators. We believe this is ultimately due to key characteristics of thedomain: highly complex operators, a need for extensive code specialization forperformance, and a desire for permissive high-level programming styles allowingproductive experimentation. The Julia language attempts to provide a moreeffective structure for this kind of programming by allowing programmers toexpress complex polymorphic behaviors using dynamic multiple dispatch overparametric types. The forms of extension and reuse permitted by this paradigmhave proven valuable for technical computing. We report on how this approachhas allowed domain experts to express useful abstractions while simultaneouslyproviding a natural path to better performance for high-level technical code.

Fast Flexible Function Dispatch in Julia