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stc-lang: A library for implicit, monadic dataflow parallelism

[ bsd3, concurrency, development, library, program ] [ Propose Tags ]

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Versions [RSS] [faq] 1.0.0
Dependencies abstract-par (>=0.3.3), aeson (>=1.2.3.0), base (>=4.7 && <5), BoundedChan (>=1.0.3.0), bytestring (>=0.10.8.2), clock (>=0.7.2), deepseq (>=1.4.3.0), hashable (>=1.2.6.1), hashtables (>=1.2.2.1), hedis (>=0.9.12), hw-kafka-client (>=2.6.0), microlens (>=0.4.8.3), microlens-aeson (>=2.2.0.2), monad-par (>=0.3.4.8), monad-par-extras (>=0.3.3), mtl (>=2.2.1), random (>=1.1), stc-lang, text (>=1.2.2.2), transformers (>=0.5.2.0), uuid-types (>=1.0.3), vector (>=0.12.0.1), yaml (>=0.8.28) [details]
License BSD-3-Clause
Copyright 2017-2019 Norman Rink, Sebastian Ertel, Justus Adam
Author Norman Rink, Sebastian Ertel, Justus Adam
Maintainer justus.adam@tu-dresden.de
Revised Revision 1 made by justus at 2019-08-01T12:03:20Z
Category Concurrency, Development
Home page https://github.com/ohua-dev/stc-lang#readme
Source repo head: git clone https://github.com/ohua-dev/stc-lang
Uploaded by justus at 2019-08-01T11:58:19Z
Distributions NixOS:1.0.0
Executables ohua-stream-bench
Downloads 397 total (5 in the last 30 days)
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Status Hackage Matrix CI
Docs not available [build log]
All reported builds failed as of 2019-08-01 [all 3 reports]

Modules

  • Control
    • Monad
      • Control.Monad.Generator
      • Control.Monad.SD
      • Control.Monad.Stream
        • Control.Monad.Stream.Chan
        • Control.Monad.Stream.Par
        • Control.Monad.Stream.PinnedChan
  • Data
    • Data.Dynamic2
    • Data.StateElement
  • Type
    • Type.Magic

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Readme for stc-lang-1.0.0

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STCLang: A library for implicit monadic dataflow parallelism

STCLang is a library that enables stateful, implicit, monadic parallel computation in Haskell. The core ideas come from the ohua project.

STCLang lets you create parallel dataflows with stateful nodes without having to explicitly wire complex graph structures. Instead the program is written with an embedded, monadic DSL and automatically transformed into a graph and executed in parallel.

On top of the base abstraction we have also built an FRP (functional reactive programming) interface. This allows you to run reactive programs on sequential streams of values and leverage pipeline parallelism to peed up computation.

We also published the theory and concepts behind this library.

Publication

We documented the principles in this library in a paper at Haskell'2019.

A link to the publication will appear here once we have one, e.t.a. is 22th of August (date of the conference). Should it be after this date now, but there's still no link, I probably forgot. In that case open an issue, shoot me an email or tweet me @justusadam_.