Difference between revisions of "Parallelism"

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''Note: you may want to read [[Parallelism vs. Concurrency]], as the terms have historically been conflated.''
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== Parallel Programming in GHC ==
  
   
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This page contains notes and information about how to use parallelism in GHC to speed up pure functions in your program.
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This page contains notes and information about how to write parallel programs in Haskell.
   
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For practicality, the content is GHC-centric at the moment, although this may change as Haskell evolves.
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You may be interested in [[GHC/Concurrency|concurrency]] instead, which would allow you to manage simultaneous IO actions.
  
   
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== Overview ==
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GHC provides multi-scale support for parallel programming, from very fine-grained, small "sparks", to coarse-grained explicit threads and locks (using concurrency), along with other models of parallel programming.
  
   
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The parallel programming models in GHC can be divided into the following forms:
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GHC provides multi-scale support for parallel programming, from very fine-grained, small "sparks" to nested data parallelism and strategies.
   
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== Getting started ==
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* Very fine grained: parallel sparks and futures, as described in the paper "[http://www.haskell.org/~simonmar/bib/multicore-ghc-09_abstract.html Runtime Support for Multicore Haskell]"
  
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* Nested data parallelism: a parallel programming model based on bulk data parallelism, in the form of the [http://www.haskell.org/haskellwiki/GHC/Data_Parallel_Haskell DPH] and [http://hackage.haskell.org/package/repa Repa] libraries for transparently parallel arrays.
  
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* Intel [http://software.intel.com/en-us/blogs/2010/05/27/announcing-intel-concurrent-collections-for-haskell-01/ Concurrent Collections for Haskell]: a graph-oriented parallel programming model.
  
   
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Speed up your code by making it run on multicore:
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The most important (as of 2010) to get to know are implicit parallelism via sparks. If you're interested in scientific programming specifically, you may also be interested in current research on nested data parallelism in Haskell.
  
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: Start with Control.Parallel ('''par''', '''pseq''')
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: [[Parallel/Reading|Learn more about parallelism]], then try using Strategies
   
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== GHC parallelism specifics ==
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=== Starting points ===
  
   
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You get access to parallelism operations by importing the library [http://www.haskell.org/ghc/docs/latest/html/libraries/base/Control-Parallel.html Control.Parallel].
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* '''Control.Parallel'''. The first thing to start with parallel programming in Haskell is the use of par/pseq from the parallel library.
 
   
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{{GHC/Multicore}}
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* '''Nested Data Parallelism'''. For an approach to exploiting the implicit parallelism in array programs for multiprocessors, see [[GHC/Data Parallel Haskell|Data Parallel Haskell]] (work in progress).
  
   
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Support for low-level parallelism features of modern processors continues to be added. As of version 7.8, GHC includes the ability to [https://ghc.haskell.org/trac/ghc/wiki/SIMD emit SIMD instructions], and also has a rudimentary ability to use [[AtomicMemoryOps|atomic memory operations]].
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=== Multicore GHC ===
  
   
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== Community ==
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{{GHC/Multicore}}
  
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* Ask questions on [[Mailing lists|Haskell Cafe]]
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* See what [https://groups.google.com/group/parallel-haskell parallel-haskell] researchers and developers are working on
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* Get the latest from the [[Parallel GHC Project]]
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* Follow [http://twitter.com/#!/parallelhaskell @parallelhaskell] on Twitter [[image:Twitter-mini.png]]
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* StackOverflow on Haskell [http://stackoverflow.com/questions/tagged/haskell%2bparallel parallelism]
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== News ==
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* 2012-04-20 [http://www.well-typed.com/blog/65 Parallel Haskell Digest 9]
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* 2012-03-02 [http://www.well-typed.com/blog/64 Parallel Haskell Digest 8]
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* 2011-12-24 [http://www.well-typed.com/blog/62 Parallel Haskell Digest 7]
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* 2011-11-21 [http://www.haskell.org/pipermail/haskell-cafe/2011-November/097008.html Job Opportunity at Parallel Scientific]
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== Tools ==
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* [[ThreadScope]] - parallel programs not getting faster? Use the ThreadScope debugger and watch those sparks fly.
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* Various [[Applications and libraries/Concurrency and parallelism|libraries]], including those for parallelism.
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== Documentation ==
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* [[Parallel/Glossary|Glossary]]
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* [[Parallel/Reading|Learning to use parallelism in Haskell]]
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* [[Parallel/Research|Current research]]
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* [http://chimera.labs.oreilly.com/books/1230000000929/index.html Parallel ... Programming in Haskell] (online book)
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== Alternative approaches ==
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* [https://www.cse.chalmers.se/edu/year/2012/course/pfp/Papers/strategies10.pdf Seq no more: Better Strategies for Parallel Haskell]
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== See also ==
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* [[:Category:Parallel|Parallel]] category
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* Parallelism [[Parallel/Research|research]]
   
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=== Related work ===
  
   
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[[Category:GHC]]
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* [[Parallel]] portal
  
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[[Category:Parallel]]
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* [[Parallel/Research|Ongoing research in Parallel Haskell]]
  
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* The Sun project to improve http://ghcsparc.blogspot.com/ GHC performance on Sparc]
  
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* A [http://www.well-typed.com/blog/38 Microsoft project to improve industrial applications of GHC parallelism].
  

Latest revision as of 12:02, 9 May 2024

Note: you may want to read Parallelism vs. Concurrency, as the terms have historically been conflated.

This page contains notes and information about how to write parallel programs in Haskell.

For practicality, the content is GHC-centric at the moment, although this may change as Haskell evolves.

Overview

GHC provides multi-scale support for parallel programming, from very fine-grained, small "sparks" to nested data parallelism and strategies.

Getting started

Speed up your code by making it run on multicore:

Start with Control.Parallel (par, pseq)
Learn more about parallelism, then try using Strategies

GHC parallelism specifics

You get access to parallelism operations by importing the library Control.Parallel.

Since 2004, GHC supports running programs in parallel on an SMP or multi-core machine. How to do it:

  • Compile your program using the -threaded switch.
  • Run the program with +RTS -N2 to use 2 threads, for example (RTS stands for runtime system; see the GHC users' guide). You should use a -N value equal to the number of CPU cores on your machine (not including Hyper-threading cores). As of GHC v6.12, you can leave off the number of cores and all available cores will be used (you still need to pass -N however, like so: +RTS -N).
  • Concurrent threads (forkIO) will run in parallel, and you can also use the par combinator and Strategies from the Control.Parallel.Strategies module to create parallelism.
  • Use +RTS -sstderr for timing stats.
  • To debug parallel program performance, use ThreadScope.

Support for low-level parallelism features of modern processors continues to be added. As of version 7.8, GHC includes the ability to emit SIMD instructions, and also has a rudimentary ability to use atomic memory operations.

Community

News

Tools

  • ThreadScope - parallel programs not getting faster? Use the ThreadScope debugger and watch those sparks fly.
  • Various libraries, including those for parallelism.

Documentation

Alternative approaches

See also

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