robinhood
future
robinhood | future | |
---|---|---|
2 | 2 | |
174 | 932 | |
0.0% | - | |
0.0 | 8.1 | |
6 months ago | 17 days ago | |
C | R | |
GNU General Public License v3.0 or later | - |
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robinhood
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Disk usage on large raid
https://github.com/cea-hpc/robinhood maybe this could work for you?
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Japan HP accidentally deleted 77TB data in Kyoto U. supercomputing system
Assuming this was a "scratch" HPC filesystem, as I'd guess, "scratch" is used advisedly -- users should be prepared to lose anything on it, not that it should happen with finger trouble. However, if I understand correctly from the comments, I'm surprised at the tools, and that the vendor was managing the filesystem. I'd expect to use https://github.com/cea-hpc/robinhood/wiki with Lustre, though I thought I'd seen a Cray presentation about tools of their own.
future
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Running Code in Parallel
Check out the future package: https://github.com/HenrikBengtsson/future
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What's faster: run simultaneously on multiple terminals, or run everything sequentially on one terminal?
If you're a fan of the tidyverse check out the furrr package, which is based on the future package. Let's you apply your map() functions in parallel very easily.
What are some alternatives?
ShellCheck - ShellCheck, a static analysis tool for shell scripts
seurat - R toolkit for single cell genomics
PiBluetoothMidSetup - Turn a raspberry pi into a Bluetooth Midi device
R-sharp - R# language is a kind of R liked vectorized language implements on .NET environment for the bioinformatics data analysis
crul - R6 based http client for R (for developers)
HoRM - Supplemental Functions and Datasets for "Handbook of Regression Methods"
hts - Hierarchical and Grouped Time Series
r2u - CRAN as Ubuntu Binaries
openxlsx - openxlsx - a fast way to read and write complex xslx files
parsel - parallel execution of RSelenium
shiny.i18n - Shiny applications internationalization made easy
randomNames - Function to generate random gender and ethnicity correct first and/or last names. Names are chosen proportionally based upon their probability of appearing in a large scale data base of real names.