Showing 4 of total 4 results (show query)
shikokuchuo
nanonext:NNG (Nanomsg Next Gen) Lightweight Messaging Library
R binding for NNG (Nanomsg Next Gen), a successor to ZeroMQ. NNG is a socket library for reliable, high-performance messaging over in-process, IPC, TCP, WebSocket and secure TLS transports. Implements 'Scalability Protocols', a standard for common communications patterns including publish/subscribe, request/reply and service discovery. As its own threaded concurrency framework, provides a toolkit for asynchronous programming and distributed computing. Intuitive 'aio' objects resolve automatically when asynchronous operations complete, and synchronisation primitives allow R to wait upon events signalled by concurrent threads.
Maintained by Charlie Gao. Last updated 1 days ago.
concurrencyhttpsipc-messagemessaging-librarynngrpcsocket-communicationsynchronization-primitivestcp-protocolwebsocketmbedtls
21.3 match 60 stars 9.81 score 28 scripts 9 dependents
dmarchette
cccd:Class Cover Catch Digraphs
Class Cover Catch Digraphs, neighborhood graphs, and relatives.
Maintained by David J. Marchette. Last updated 3 years ago.
3.3 match 1 stars 2.12 score 131 scriptsshikokuchuo
mirai:Minimalist Async Evaluation Framework for R
Designed for simplicity, a 'mirai' evaluates an R expression asynchronously in a parallel process, locally or distributed over the network. The result is automatically available upon completion. Modern networking and concurrency, built on 'nanonext' and 'NNG' (Nanomsg Next Gen), ensures reliable and efficient scheduling over fast inter-process communications or TCP/IP secured by TLS. Distributed computing can launch remote resources via SSH or cluster managers. An inherently queued architecture handles many more tasks than available processes, and requires no storage on the file system. Innovative features include support for otherwise non-exportable reference objects, event-driven promises, and asynchronous parallel map.
Maintained by Charlie Gao. Last updated 2 days ago.
asyncasynchronous-tasksconcurrencydistributed-computinghigh-performance-computingparallel-computing
0.5 match 217 stars 11.94 score 130 scripts 7 dependents
wlandau
crew:A Distributed Worker Launcher Framework
In computationally demanding analysis projects, statisticians and data scientists asynchronously deploy long-running tasks to distributed systems, ranging from traditional clusters to cloud services. The 'NNG'-powered 'mirai' R package by Gao (2023) <doi:10.5281/zenodo.7912722> is a sleek and sophisticated scheduler that efficiently processes these intense workloads. The 'crew' package extends 'mirai' with a unifying interface for third-party worker launchers. Inspiration also comes from packages. 'future' by Bengtsson (2021) <doi:10.32614/RJ-2021-048>, 'rrq' by FitzJohn and Ashton (2023) <https://github.com/mrc-ide/rrq>, 'clustermq' by Schubert (2019) <doi:10.1093/bioinformatics/btz284>), and 'batchtools' by Lang, Bischel, and Surmann (2017) <doi:10.21105/joss.00135>.
Maintained by William Michael Landau. Last updated 1 days ago.
0.5 match 136 stars 11.19 score 243 scripts 2 dependents