shakedown.social is one of the many independent Mastodon servers you can use to participate in the fediverse.
A community for live music fans with roots in the jam scene. Shakedown Social is run by a team of volunteers (led by @clifff and @sethadam1) and funded by donations.

Administered by:

Server stats:

285
active users

#parallel

0 posts0 participants0 posts today

#WritingWonders 5 - Does your antagonist have any moral boundaries they would never cross?

In #Parallel Lines, Davina's mission --her reason for being! -- is to prevent anyone from making changes that would alter the consistency and history of the universe we live in.

So: no boundaries. She's friendly and BIble-quoting ... but if you try to alter history or the future, she will hunt you down and slaughter you without remorse.

future 1.31.0 on CRAN. Mainly cleaning up legacy code blocking me from adding new, exciting features.

Now, if you still rely on

plan(multiprocess)

, which has been deprecated since Oct 2020 (sic!), for parallelization, it'll now run in sequential mode, and you'll get heaps of deprecation warnings. If that doesn't do it, and you keep using 'multiprocess', I've got more aces up my sleeve. Just saying 🤠

future.futureverse.org/

future.futureverse.orgUnified Parallel and Distributed Processing in R for EveryoneThe purpose of this package is to provide a lightweight and unified Future API for sequential and parallel processing of R expression via futures. The simplest way to evaluate an expression in parallel is to use `x %<-% { expression }` with `plan(multisession)`. This package implements sequential, multicore, multisession, and cluster futures. With these, R expressions can be evaluated on the local machine, in parallel a set of local machines, or distributed on a mix of local and remote machines. Extensions to this package implement additional backends for processing futures via compute cluster schedulers, etc. Because of its unified API, there is no need to modify any code in order switch from sequential on the local machine to, say, distributed processing on a remote compute cluster. Another strength of this package is that global variables and functions are automatically identified and exported as needed, making it straightforward to tweak existing code to make use of futures.