Applications and libraries/Concurrency and parallelism
Concurrent and Parallel Programming
Haskell has been designed for parallel and concurrent programming since its inception. In particular, Haskell's purity greatly simplifies reasoning about parallel programs. This page lists libraries and extensions for programming concurrent and parallel applications in Haskell. See also the research papers on parallel and concurrent Haskell.
Collected tutorials and information on multicore programming with Haskell:
- 1 SMP Haskell
- 2 Concurrency
- 3 Concurrent channels
- 4 Software transactional memory
- 5 Parallel strategies
- 6 Data Parallel Haskell
- 7 Unified events and threads
- 8 Feedback-directed implicit parallelism
- 9 Parallel Haskell
- 10 Distributed Haskell
- 11 MPI
- 12 Distributed Haskell: Ports
- 13 Modelling concurrent and distributed systems
- 14 Communicating Haskell Processes
- Multiprocessor GHC
- As of GHC 6.5, GHC supports running programs in parallel on an SMP or multicore machine, and has been used successfully on up to 40 cpus.
- Concurrent Haskell
- GHC has supported concurrency via forkIO and MVars for more than a
decade, and its threading support is very fast.
- Wrapped Concurrency
- A wrapper around Control.Concurrency and Control.Exception that provides versions of forkIO that have more guarantees.
- channels allow threads to pass messages to each other
Software transactional memory
- Software Transactional Memory
- GHC supports a sophisticated version of software transactional memory. Software Transactional Memory (STM) is a new way to coordinate concurrent threads.
- The paper Composable memory transactions.
- The paper Lock-free data structures using Software Transactional Memory in Haskell gives further examples of concurrent programming using STM.
- Parallel evaluation stratagies may be hinted, which is a much lighter way to achieve paralellism than to use explicit concurrency primitives.
- Documentation. -- Broken?
- The HEAD version of the same contains more information.
- The original paper
Data Parallel Haskell
- Data Parallel Haskell
- Implicitly parallel, high performance (nested) arrays, supporting large multicore programming.
Unified events and threads
- User-level events and threads
- Ultra lightweight, user level threads for GHC Haskell, layered over epoll. Supports up to 10 million lightweight threads. Experimental.
Feedback-directed implicit parallelism
- GpH: Glasgow Parallel Haskell
- A complete, GHC-based implementation of the parallel Haskell extension GpH and of evaluation strategies is available. Extensions of the runtime-system and language to improve performance and support new platforms are under development.
- GdH: Glasgow Distributed Haskell
- GdH supports distributed stateful interactions on multiple locations. It is a conservative extension of both Concurrent Haskell and GpH, enabling the distribution of the stateful IO threads of the former on the multiple locations of the latter. The programming model includes forking stateful threads on remote locations, explicit communication over channels, and distributed exception handling.
- Mobile Haskell (mHaskell)
- Mobile Haskell supports both strong and weak mobility of computations across open networks. The mobility primitives are higher-order polymorphic channels. Mid-level abstractions like remote evaluation, analogous to Java RMI, are readily constructed. High-level mobility skeletons like mobile map and mobile fold encapsulate common patterns of mobile computation.
- Eden extends Haskell with a small set of syntactic constructs for explicit process specification and creation. While providing enough control to implement parallel algorithms efficiently, it frees the programmer from the tedious task of managing low-level details by introducing automatic communication (via head-strict lazy lists), synchronisation, and process handling.
- hMPI is an acronym for HaskellMPI. It is a Haskell binding conforming to MPI (Message Passing Interface) standard 1.1/1.2. The programmer is in full control over the communication between the nodes of a cluster.
Distributed Haskell: Ports
- The Haskell Ports Library (HPL)
- Ports are an abstraction for modelling variables whose values evolve over time without the need to resort to mutable variable, such as IORefs. More precisely, a port represents all values that a time-dependent variable successively takes as a stream, where each element of the stream corresponds to a state change - we can also say that a port represents a time series. Moreover, a port supports concurrent construction of the time series, or stream of values.
Modelling concurrent and distributed systems
- HCPN: Haskell-Coloured Petri Nets
- Haskell-Coloured Petri Nets (HCPN) are an instance of high-level Petri Nets, in which anonymous tokens are replaced by Haskell data objects (and transitions can operate on that data, in addition to moving it around). This gives us a hybrid graphical/textual modelling formalism for Haskell, especially suited for modelling concurrent and distributed systems.
Communicating Haskell Processes
- CHP: Communicating Haskell Processes
- CHP is built on the ideas of CSP (Communicating Sequential Processes), featuring encapsulated parallel processes (no shared data!) communicating over synchronous channels. This is a very composable mode that also allows choice on communications, so that a process may offer to either read on one channel or write on another, but will only take the first that is available.