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Parallelism

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1 Parallel Programming in GHC

This page contains notes and information about how to use parallelism in GHC.

You may be interested in concurrency instead. Have a look there too.

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.

The parallel programming models in GHC can be divided into the following forms:

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.

1.1 Starting points

  • Nested Data Parallelism. For an approach to exploiting the implicit parallelism in array programs for multiprocessors, see Data Parallel Haskell (work in progress).

1.2 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.

1.3 Related work