We had our first DenHUG meeting yesterday. It was just Ben Atkin and myself, but we had a good chat about Haskell and why we're interested in it. We're taking different approaches to learning Haskell, Ben is downloading and studying applications written in Haskell, while I'm reading Real World Haskell, and we're both experimenting as we explore the Haskell ecosystem.

Ben asked me what my expectations were for the DenHUG meetup group. I told him that it was an experiment to see if it would help me learn Haskell. This got me to thinking that I should probably have better defined goals for the group. Here's a rough cut:

• Learn Haskell and explore it's potential.
• Meet others interested in Haskell, and more generally, Functional Programming.
• Determine where Functional Programming works better then other programming paradigms and where it is a poor fit.
• Find out why one would choose Haskell over functional languages like Erlang, Ocaml, or Scheme.

Data Parallel Haskell: a status report presents promising results from the project. While still a work in progress, good multi-core speedups have been demonstrated. The approach maps the data parallel computations to a gang of threads whose execution can be interleaved with task parallel threads by the scheduler.

MongoDB is a scalable, high-performance, open source, schema-free, documented oriented database written in C++. It has interfaces for Haskell, Python, and a number of other languages. "Documents" consist of binary JSON like data structures called BSON. It looks promising for real time analytics.

The Eucalyptus Open-source Cloud-computing System provides a way for organizations to build private cloud computing infrastructures to flexibly provide computer resources to their users. Eucalyptus implements Amazon's EC2 and S3 cloud computing interfaces and runs user applications on virtual machines on a computer cluster for isolation and redundancy. It features a virtual network so that user applications need have no knowledge of the physical network.

Cassandra is a distributed database for structured data developed by the facebook team. They open sourced it in 2008 and is now an Apache incubator project and used by a number of other companies for data sets as large as 150 TB. It's written in Java with bindings for a number of other languages including Python, Haskell, and Erlang. Combining Amazon's Dynamo distribution model with Google's Big Table data model, Cassandra looks promising for Ultra Large Scale (ULS) systems.

Darcs is an interesting distributed version control system based upon a theory of patches and written in Haskell . I'm considering using Haskell for future projects and will use darcs for revision control for some work I'm doing to see how a non-trivial Haskell application performs in everyday use.

Things are getting very busy at work, with travel that conflicts with PyCon 2010, and I've had to cancel my talk there. I was looking forward to it. Maybe next year.

I've been interested in the Palm Pre and WebOS since they debuted at the 2009 CES, but it was only available on Sprint and I prefer Verizon. The Palm Pre Plus is now available on Verizon so I've upgraded to it from my trusty Palm Treo. The graphics are stunning, touch screen interaction intuitive, and mult-tasking outstanding. The biggest down side is the unimpressive battery life, it's been making it through the day with moderate use, but there isn't much reserve. I think WebOS has a lot of potential, but it'll take some time to get used to doing some things differently than Palm OS.

I've been doing some thinking about Cyber Renaissance and the system management problems the company is trying to solve. It's still an early stage startup and we're exploring some ideas about using autonomic clusters of computers to do useful work. This is an interesting problem domain, and may prove to be profitable.

We're looking at using a functional programming language such as Erlang or Haskell to implement this since they promise improved reliability and effective use of the multi-core processors that are now mainstream. As we develop our ideas, we'll experiment with the functional programming paradigm to see how well it fits both the problem domain and our brains.