Parallel GHC Project
(→The Parallel Haskell Digest: part 2)
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=== Cloud Haskell ===
=== Cloud Haskell ===
We are continuing work on the new Cloud Haskell implementation, [http://sneezy.cs.nott.ac.uk/fun/2012-02/coutts-2012-02-28.pdf recently presented] by Duncan Coutts. Lately, we have been focused on reducing message latency. This consists of work in three areas: improving binary serialisation, investigating the implications of using Chan and MVar to pass messages between threads, and perhaps improving the Haskell network library implementation to compete better with a direct C implementation.
The reimplementation of Cloud Haskell is now [http://hackage.haskell.org/package/distributed-process avaiable from Hackage] and in a state where it is ready for serious experiments. Compared to the prototype it is much faster; it can run on [http://hackage.haskell.org/package/network-transport multiple kinds of network];
it has backends to support different environments (like cluster or cloud, with a proof-of-concept [http://hackage.haskell.org/package/distributed-process-azure backend for Azure]);
has a new system for dealing with node disconnect and reconnect, and a more [https://github.com/haskell-distributed/distributed-process/blob/master/doc/semantics/CloudHaskellSemantics.pdf precisely defined semantics]; supports [http://hackage.haskell.org/package/distributed-static composable], [http://hackage.haskell.org/package/rank1dynamic polymorphic] serialisable closures; and internally the code is better structured and easier to work with.
For more information on our implementation, see the [https://github.com/haskell-distributed/distributed-process distributed-process GitHub page] and particularly the updated [https://github.com/haskell-distributed/distributed-process/wiki/New-backend-and-transport-design design document], which incorporates feedback on our initial design proposal.
The wiki lists some [https://github.com/haskell-distributed/distributed-process/wiki/Important-Open-Issues important open issues] of the implementation; the semantics document mentioned above lists some important open semantic issues.
== Project artefacts ==
== Project artefacts ==
Revision as of 12:19, 12 November 2012
In the last few years GHC has gained impressive support for parallel programming on commodity multi-core systems. In addition to traditional threads and shared variables, it supports pure parallelism, software transactional memory (STM), and data parallelism. With much of this research and development complete, the next stage is to get the technology into more widespread use.
This project aims to do the engineering work to solve whatever remaining practical problems are blocking organisations from making serious use of parallelism with GHC. The driving force is the applications rather than the technology.
The project involves a partnership with six groups from commercial and scientific organisations. Over the course of two years these groups are applying parallel Haskell in their specific domains. They are being supported by GHC HQ and Well-Typed who are providing advice on Haskell tools and techniques, and applying engineering effort to resolve any issues that are hindering these groups' progress.
The project is being coordinated by Well-Typed and they are providing the bulk of the support and engineering effort. The project started in the summer of 2010.
2 Project News
2.1 ThreadScope and friends
We have been continuing our work to make ThreadScope more helpful and informative in tracking down your parallel and concurrent Haskell performance problems. We now have the ability to collect heap statistics from the GHC runtime system and present them in ThreadScope. These features will be available for users of a recent development GHC (7.5.x) or the eventual 7.6 release. In addition to heap statistics, we have been working on collecting information from hardware performance counters, more specifically adding support for Linux Perf Events. This could be useful for studying IO-heavy programs, the idea being to visualise system calls as being distinct from actual execution of Haskell code.
2.2 Cloud Haskell
The reimplementation of Cloud Haskell is now avaiable from Hackage and in a state where it is ready for serious experiments. Compared to the prototype it is much faster; it can run on multiple kinds of network; it has backends to support different environments (like cluster or cloud, with a proof-of-concept backend for Azure); has a new system for dealing with node disconnect and reconnect, and a more precisely defined semantics; supports composable, polymorphic serialisable closures; and internally the code is better structured and easier to work with.
The wiki lists some important open issues of the implementation; the semantics document mentioned above lists some important open semantic issues.
3 Project artefacts
Some of the work by our project partners is available to the public
|mightttpd2||IIJ||File/CGI server on top of Warp||version 2.5.7 released 2012-04-05|
|webserver||IIJ||HTTP server library||version 0.4.6 released 2011−10−05|
|wai-app-file-cgi||IIJ||File/CGI WAI application (used by Mighttpd)||version 0.5.8 released 2012-04-05|
|wai-logger||IIJ||Logging system for WAI (used by Mighttpd)||version 0.1.4 released 2012-02-13|
|http-date||IIJ||Fast parser and formatter for HTTP Date||version 0.0.2 released 2012-02-17|
|dns||IIJ||DNS library||version 0.2.0 released 2011−08−31|
|iproute||IIJ||IP routing table||version 1.2.5 released 2012-04-02|
|domain-auth||IIJ||Library for Sender Policy Framework, SenderID, DomainKeys and DKIM.||version 0.2.0 released 2011−08-31|
|RPF||IIJ||Receiver Policy Framework (milter)||version 0.2.0 released 2011−08-31|
In addition to helping the participating organisations, the project will whenever possible make improvements to libraries and tools that are useful to Haskell users more generally.
|multiprocess Threadscope||profiling of multi-process or distributed Haskell systems such as client/server or MPI programs.||in progress|
|LFG||Haskell implementation of some pseudo random number generators from the SPRNG library||testing|
|SPRNG binding||Haskell wrapper around SPRNG||in progress|
|ThreadScope improvements||new spark profiling tools, GUI enhancements, bug fixes||version 0.2.1 released 2012-01-14|
|ghc-events improvements||spark events support||version 0.4.0.0 released 2012-01-14|
|gtk2hs maintenance & release||GHC 7.2 support||version 0.12.2 released 2011-11-13|
|Haskell-MPI||Haskell bindings to C MPI library||version 1.2.1 released 2012-02-15|
|GHC RTS improvements||#4449 - GHC 7 can't do IO when daemonized||fixed in 7.0.x branch|
|#4504 - "awaitSignal Nothing" does not block thread with -threaded||fixed in 7.0.2|
|#4512 - EventLog does not play well with forkProcess||fixed in 7.0.x branch|
|#4514 - IO manager can deadlock if a file descriptor is closed behind its back||fixed in 7.0.x branch|
|#4854 - Validating on a PPC Mac OS X: Fix miscellaneous errors and warnings||fixed in 7.0.x branch|
|c2hs improvements||marshalling functions now can have arguments supplied to them.||version 0.16.3 released 2011−03−24|
The project will also aim to document existing tools and parallel programming practices, making them accesible to a wider public.
|ThreadScope Tour||a short guide to using ThreadScope to help analyse parallel program performance||unveiled 2012-01-14|
|submissions to TMR 19||Mighttpd – a High Performance Web Server in Haskell (Kazu Yamamoto)||submitted|
|High Performance Haskell with MPI (Bernie Pope and Dmitry Astapov)||submitted|
|Parallel Haskell Portal||one-stop resource oriented for users of parallelism and concurrency in Haskell||unveiled 2011−04−20|
4 The Parallel Haskell Digest
We have been publishing a regular newsletter containing project news, other parallel news from around the Haskell community and short "Word of the Month" articles giving brief intrductions to important concepts in parallelism.
The back issues are here:
- Parallel Haskell Digest 1 with word of the month spark
- Parallel Haskell Digest 2 with word of the month thread of execution
- Parallel Haskell Digest 3 with word of the month parallel arrays
- Parallel Haskell Digest 4 with words of the month par and pseq
- Parallel Haskell Digest 5 with word of the month strategy
- Parallel Haskell Digest 6 with word of the month dataflow as in dataflow parallelism
- Parallel Haskell Digest 7 (catching up on community news)
- Parallel Haskell Digest 8 with word of the month MVar
- Parallel Haskell Digest 9 with the word of the month transaction
- Parallel Haskell Digest 10 with the word of the month channel
- Parallel Haskell Digest 11 with the word of the month actor (see part 2, A Cloud Haskell Appetiser)
5 Getting involved
The best starting point to get involved is to join the mailing list. Note that the list is for parallel Haskell generally, not just the Parallel GHC Project.
6 Participating organisations
- Cloudy Bayes: Hierarchical Bayesian modeling in Haskell
- The Cloudy Bayes project aims to develop a fast Bayesian model fitter that takes advantage of modern multiprocessor machines. It will support model descriptions in the BUGS model description language (WinBUGS, OpenBUGS, and JAGS). It will be implemented as an embedded domain specific language (EDSL) within Haskell. A wide range of model hierarchical Bayesian model structures will be possible, including many of the models used in medical, ecological, and biological sciences.
- Cloudy Bayes will provide an easy to use interface for describing models, running Monte Carlo Markov chain (MCMC) fitters, diagnosing performance and convergence criteria as it runs, and collecting output for post-processing. Haskell's strong type system will be used to ensure that model descriptions make sense, providing a fast, safe development cycle.
- IIJ Innovation Institute Inc.
- Haskell is suitable for many kinds of domain, and GHC's support for lightweight threads makes it attractive for concurrency applications. An exception has been network server programming because GHC 6.12 and earlier have an IO manager that is limited to 1024 network sockets. GHC 7 has a new IO manager implementation that gets rid of this limitation.
- This project will implement several network servers to demonstrate that Haskell is suitable for network servers that handle a massive number of concurrent connections.
- Los Alamos National Laboratory
- This project will use parallel Haskell to implement high-performance Monte Carlo algorithms, a class of algorithms which use randomness to sample large or otherwise intractable solution spaces. The initial goal is a particle-based MC algorithm suitable for modeling the flow of radiation, with application to problems in astrophysics. From this, the project is expected to move to identification of suitable abstractions for expressing a wider variety of Monte Carlo algorithms, and using models for different physical phenomena.
- Willow Garage Inc.
- Distributed Rigid Body Dynamics in ROS
- Willow Garage seeks a high-level representation for a distributed rigid body dynamics simulation, capable of excellent parallel speedup on current and foreseeable hardware, yet linking to existing optimized libraries for low-level message passing and matrix math.
- This project will drive API, performance, and profiling tool requirements for Haskell's interface to the Message Passing Interface (MPI) specification, an industry-standard in High Performance Computing (HPC), as used on clusters of many nodes.
- Competing internal initiatives use C++/MPI and CUDA directly.
- Willow Garage aims to lay the groundwork for personal robotics applications in everyday life. ROS (Robot Operating System) is an open source, meta-operating system for your robot.
- This project is to demonstrate parallel Haskell technology using the example of graph algorithms in large graphs representing social networks. The current work is on parallel versions of the Bron-Kerbosch algorithm for finding maximal cliques in a graph. The initial goal is to demonstrate good speedups on multi-core and the overall aim to demonstrate good speedups of a distributed version of the algorithm using Cloud Haskell.
- VETT are working on a transaction processing application using Cloud Haskell. More details will be available shortly.