Currently having the Malatesta server computing the #SVD decomposition of a 1822461 by 1822461 matrix.
Using #julialang KrylovKit.jl it works so smoothly it's magic.
For a few (<10) svd vals it runs so quickly. Pushing it to 100 now, let's see! (Main limit now is the server's RAM, which was never that big. Thinking to move to #JuliaHub for those juicy machines)
a familiar name on the front of this F1 car 🏎️🏎️🏎️😂
I'm putting together a #webinar for Thursday that goes through uploading, analyzing in #parallel #distributed #julialang, and plotting results from 390+ #parquet files in #JuliaHub.
I'll be doing lots of risky live demo things with ~50GB of #data — should be fun!
Sign up here: https://us02web.zoom.us/webinar/register/5816684248926/WN_17r8rzTGQVqfcrAVhKHsgw
#webinar #parallel #distributed #julialang #parquet #juliahub #data
#JuliaBeginners #JuliaLang #JuliaTipOfTheDay
2022-11-21
The search on the JuliaHub site (https://juliahub.com/ui/Search) is an incredible resource.
Came across a macro in a snippet of code, and need to know where the macro is from? Try searching for it via the Symbols tab, filtering by "definition" and "macro".
You can also search across the documentations of all registered packages, regex-search through public Julia code, etc.
#juliabeginners #julialang #juliatipoftheday #juliahub #search