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Kanal tas-sors @linuxgram · Post #17841 · Fra 19

📰 AI Helped Uncover A "50-80x Improvement" For Linux's IO_uring Linux block maintainer and IO_uring lead developer Jens Axboe recently was debugging some slowdowns in the AHCI/SCSI code with IO_uring usage. When turning to Claude AI to help in sorting through the issue, patches were devised that can deliver up to a "literally yield a 50-80x improvement on the io_uring side for idle systems." The code is on its way to the Linux kernel... 🔗 Source: https://www.phoronix.com/news/AI-50-80x-IO-uring #linux#kernel

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Tfittxija: #cartopy

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djangoproject

@djangoproject · Post #423 · 26/08/2017 08:39

http://scitools.org.uk/iris/docs/latest/userguide/index.html Iris seeks to provide a powerful, easy to use, and community-driven Python library for analysing and visualising #meteorological and #oceanographic data sets. With Iris you can: Use a single #API to work on your data, irrespective of its original format. Read and write (CF-)netCDF, GRIB, and PP files. Easily produce graphs and maps via integration with #matplotlib and #cartopy.

djangoproject

@djangoproject · Post #424 · 26/08/2017 08:43

http://scitools.org.uk/cartopy/docs/latest/index.html Cartopy is a Python package designed to make drawing maps for data analysis and visualisation as easy as possible. #Cartopy makes use of the powerful #PROJ.4, #numpy and #shapely libraries and has a simple and intuitive drawing interface to #matplotlib for creating publication quality maps. Some of the key features of cartopy are: object oriented projection definitions point, line, vector, polygon and image transformations between projections integration to expose advanced mapping in matplotlib with a simple and intuitive interface powerful vector data handling by integrating shapefile reading with Shapely capabilities