Difference between revisions of "Parallelism"
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In Haskell we provide two ways to achieve parallelism: |
In Haskell we provide two ways to achieve parallelism: |
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| − | * Pure parallelism, which can be used to speed up |
+ | * [[Pure]] parallelism, which can be used to speed up non-IO parts of the program. |
| − | * Concurrency, which can be used for parallelising IO. |
+ | * [[Concurrency]], which can be used for parallelising IO. |
| − | Pure |
+ | Pure parallelism ([https://hackage.haskell.org/package/parallel/docs/Control-Parallel.html <code>Control.Parallel</code>]): Speeding up a pure computation using multiple processors. Pure parallelism has these advantages: |
* Guaranteed deterministic (same result every time) |
* Guaranteed deterministic (same result every time) |
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| − | * no [ |
+ | * no [http://en.wikipedia.org/wiki/Race_condition race conditions] or [http://en.wikipedia.org/wiki/Deadlock deadlocks] |
| − | + | Concurrency ([https://hackage.haskell.org/package/base/docs/Control-Concurrent.html <code>Control.Concurrent</code>]): Multiple threads of control that execute "at the same time". |
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* Threads are in the IO monad |
* Threads are in the IO monad |
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* IO operations from multiple threads are interleaved non-deterministically |
* IO operations from multiple threads are interleaved non-deterministically |
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* communication between threads must be explicitly programmed |
* communication between threads must be explicitly programmed |
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* Threads may execute on multiple processors simultaneously |
* Threads may execute on multiple processors simultaneously |
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| − | * Dangers: [ |
+ | * Dangers: [http://en.wikipedia.org/wiki/Race_condition race conditions] and [http://en.wikipedia.org/wiki/Deadlock deadlocks] |
| − | Rule of thumb: use |
+ | Rule of thumb: use pure parallelism if you can, concurrency otherwise. |
== Starting points == |
== Starting points == |
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| − | * |
+ | * [https://hackage.haskell.org/package/parallel/docs/Control-Parallel.html <code>Control.Parallel</code>]: The first thing to start with parallel programming in Haskell is the use of <code>par</code> and <code>pseq</code> from the [https://hackage.haskell.org/package/parallel <code>parallel</code>] library. Try the Real World Haskell [http://book.realworldhaskell.org/read/concurrent-and-multicore-programming.html chapter on parallelism and concurrency]. The parallelism-specific parts are in the second half of the chapter. |
| − | * If you need more control, try Strategies or perhaps the |
+ | * If you need more control, try [https://hackage.haskell.org/package/parallel/docs/Control-Parallel-Strategies.html <code>Strategies</code>] or perhaps the monadic type [https://hackage.haskell.org/package/monad-par/docs/Control-Monad-Par.html <code>Par</code>]. |
== Multicore GHC == |
== Multicore GHC == |
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Latest revision as of 21:38, 3 May 2024
Parallelism is about speeding up a program by using multiple processors.
In Haskell we provide two ways to achieve parallelism:
- Pure parallelism, which can be used to speed up non-IO parts of the program.
- Concurrency, which can be used for parallelising IO.
Pure parallelism (Control.Parallel): Speeding up a pure computation using multiple processors. Pure parallelism has these advantages:
- Guaranteed deterministic (same result every time)
- no race conditions or deadlocks
Concurrency (Control.Concurrent): Multiple threads of control that execute "at the same time".
- Threads are in the IO monad
- IO operations from multiple threads are interleaved non-deterministically
- communication between threads must be explicitly programmed
- Threads may execute on multiple processors simultaneously
- Dangers: race conditions and deadlocks
Rule of thumb: use pure parallelism if you can, concurrency otherwise.
Starting points
Control.Parallel: The first thing to start with parallel programming in Haskell is the use ofparandpseqfrom theparallellibrary. Try the Real World Haskell chapter on parallelism and concurrency. The parallelism-specific parts are in the second half of the chapter.- If you need more control, try
Strategiesor perhaps the monadic typePar.
Multicore GHC
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.
Alternative approaches
- Nested data parallelism: a parallel programming model based on bulk data parallelism, in the form of the DPH and Repa libraries for transparently parallel arrays.
- monad-par and LVish provide Par monads that can structure parallel computations over "monotonic" data structures, which in turn can be used from within purely functional programs.
- [OLD] Intel Concurrent Collections for Haskell: a graph-oriented parallel programming model.