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future.p2p - A Peer-to-Peer Compute Cluster via Futureverse

Implementation of the 'Future' API <doi:10.32614/RJ-2021-048> that resolves futures on a peer-to-peer ('P2P') compute environment. By using this future backend, you and your friends can share your spare compute resources with each other.

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distributed-computingfuturefutureversep2pparallelparallel-computing

5.77 score 15 stars 4 scripts

marshal - Framework to Marshal Objects to be Used in Another R Process

Some types of R objects can be used only in the R session they were created. If used as-is in another R process, such objects often result in an immediate error or in obscure and hard-to-troubleshoot outcomes. Because of this, they cannot be saved to file and re-used at a later time. They can also not be exported to a worker in parallel processing. These objects are sometimes referred to as non-exportable or non-serializable objects. One solution to this problem is to use "marshalling" to encode the R object into an exportable representation that then can be used to re-create a copy of that object in another R process. This package provides a framework for marshalling and unmarshalling R objects such that they can be transferred using functions such as serialize() and unserialize() of base R.

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marshallingparallelserialization

3.13 score 15 stars 18 scripts

future.tools - Tools for Working with Futures

Tools for Working with Futures.

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parallel-computingparallel-programming

2.00 score 1 stars 3 scripts

doFuture.tests.extra - Extra Test Sets for the 'doFuture' Package

Runs examples of packages that use 'foreach' and '%dopar%' for parallelization, where 'doFuture' is used as the 'foreach' adapter making it possible to use any future backend for parallelization. The package tests use these tools to test 'doFuture' with 'foreach'-based examples from packages 'BiocParallel', 'caret', 'doParallel', 'glmnet', 'NMF', 'plyr', and 'TSP'. These tests are run with many known future backends.

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futureverseparalleltestsuite

1.70 score