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

Awkward Array is a library for performing NumPy-like computations on nested,variable-sized data, enabling array-oriented programming on arbitrary datastructures in Python. However, imperative (procedural) solutions can sometimesbe easier to write or faster to run. Performant imperative programming requirescompilation; JIT-compilation makes it convenient to compile in an interactivePython environment. Various functions in Awkward Arrays JIT-compile a user'scode into executable machine code. They use several different techniques, butreuse parts of each others' implementations. We discuss the techniques used toachieve the Awkward Arrays acceleration with JIT-compilation, focusing onRDataFrame, cppyy, and Numba, particularly Numba on GPUs: conversions ofAwkward Arrays to and from RDataFrame; standalone cppyy; passing Awkward Arraysto and from Python functions compiled by Numba; passing Awkward Arrays toPython functions compiled for GPUs by Numba; and header-only libraries forpopulating Awkward Arrays from C++ without any Python dependencies.

Awkward Just-In-Time (JIT) Compilation: A Developer's Experience