GHC HQ and Well-Typed are pleased to report that work has started on the MSR-funded project to push the real-world use of parallel Haskell.

We will be working with four industrial partners over the next two years, with the aim of demonstrating that parallel Haskell can be employed successfully in industrial projects.

The participating organizations are:

Dragonfly (New Zealand)

IIJ Innovation Institute Inc. (Japan)

Los Alamos National Laboratory (USA)

Willow Garage Inc. (USA)

Each group is working on their own project, applying parallel Haskell and their domain-specific expertise. In addition to providing advice on Haskell tools and techniques, we will work with these partners to identify and resolve any issues that are hindering progress. We are prepared to handle issues covering anything from the compiler and runtime system, through to platform, tool and library problems.

All the participants are working on complex, real-world problems. Three projects involve scientific problems, and the fourth involves network servers. Three of the projects are targeting single-node SMP systems, while the fourth is targeting clusters. In two cases, Haskell will be directly pitted against existing code written in C or C++.

Project progress reports will be posted to the Well-Typed blog and to Parallel Haskell mailing list.

Dragonfly

www.dragonfly.co.nz

Participants: Finlay Thompson, Edward Abraham

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.

www.iij-ii.co.jp

Participants: Kazu Yamamoto

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. The upcoming 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

www.lanl.gov

Participants: Michael Buksas, Timothy M. Kelley

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

www.willowgarage.com

Participants: Ryan Grant