PLDI 2010 Trip Report

In June, I attended my first "big" academic conference Programming Languages Design and Implementation (PLDI 2010) in Toronto. I attended the conference, because I presented a paper that I wrote with Don Syme as a result of my internship at Microsoft Research, but I'll write more about that shortly (and thanks to MSR for partly supporting my attendance at the conference!)

As far as I understand it, the focus of the conference is more on implementation. Many people believe that the current programming languages are good enough and we need to make sure that they run well (e.g. compilers optimize code to run better on multi-core) and that we need better tools for working with them (e.g. automatic verification of the code we write), so these areas were the main focus of the conference. However, there were some very interesting talks on the design of programming languages, which is an area that I personally find more interesting...

ASP.NET and F# (I.) - Creating MVC web applications in F#

Some time ago, I wrote a couple of examples of developing web applications in F# using ASP.NET. Since then, the F# language and runtime has changed a little bit and there are also new technologies available in ASP.NET, so I thought I'd write a more up-to-date article on this topic. In this article, I'll present a simple "demo" F# web application that you can use as a starting point when creating your own projects (you'll also find a convenient Visual Studio 2010 template below). The article shows the following interesting things:

• ASP.NET MVC - We're going to use ASP.NET MVC Framework to create the web application. As the article name suggests, most of the actual program code including models and controllers will be implemented in F#.
• F# LINQ to SQL - The application uses a sample Northwind database and we'll write queries for selecting data from the database using LINQ support that's available in the F# PowerPack.
• F# features - The application also uses some nice F# features that are quite useful for developing web applications. We'll use modules and records to implement the model and we'll also use advanced meta-programming features for constructing LINQ queries.

If you want to use F# for creating an MVC application, you have a few options. It should be possible to create the web application solely as an F# project. However, we'll use a more convenient approach. We'll create a standard C# MVC project and move all the actual implementation to an F# library. We'll look at the application structure shortly. The following screenshot shows a page that lists products in the Northwind database:

Accelerator and F# (IV.): Composing computations with quotations

In this article series, we're talking about the Accelerator project and I'm presenting an F# library that I implemented, which allows you to use Accelerator [references] in a more sophisticated way. We've seen two examples of using Accelerator directly (see also introduction and Game of Life). In the previous article I introduced my F# library for working with Accelerator. We've seen F# functions from the DataParallel module, we implemented an algorithm that rotates an image using these functions and finally, we've seen that we can take this ordinary F# code and run it using Accelerator. This is all possible thanks to F# quotations, which we can use to get an AST (a source code) of an F# function we wrote (if the function is marked in some special way).

In this part of the series, we're going to look at working with quotations explicitly. We'll use meta-programming techniques to work with Accelerator. Meta-programming means writing programs that manipulate with other programs or pieces of code. This is exactly what we're going to do in this article. We'll write an F# function (running on CPU) that builds a program, which we'll then run using Accelerator.

This is quite interesting approach, which isn't possible when we call Accelerator methods as standard F# functions or .NET methods. The benefit is that we'll clearly see which parts of program run on CPU and what parts execute on GPU or using X64 multi-core target. We could also perform more complicated optimizations with the code (because this wouldn't affect the readability). Just for your reference, here is the list of articles in this series in case you missed some of them:

• Accelerator and F# (I.): Introduction and calculating PI
• Accelerator and F# (II.): The Game of Life on GPU
• Accelerator and F# (III.): Data-parallel programs using F# quotations
• Accelerator and F# (IV.): Composing computations with quotations

However, enough with theory and let's take a look at some code samples! This time, we'll implement blurring of an image (also called convolution). Another example how to write this in F# using Accelerator is Satnam Singh's blog post [4]. Our example will be different, because we'll write the code as standard F# program and then have it translated to Accelerator automatically using quotations. We'll also talk about the architecture of the library that we're using and look at some performance results.

Accelerator and F# (III.): Data-parallel programs using F# quotations

If you've been following this article series, you already know that Accelerator is a MSR library [1, 2] that allows you to run code in parallel on either multi-core CPU or using shaders on GPU (see introduction). We also discussed a direct way to use Accelerator from F# (by calling Accelerator methods directly) and implemented Conway's Game of Life. In this article, we'll look at more sophisticated way of using Accelerator from F#. We'll introduce F# quotations and look at translating 'normal' F# code to use Accelerator.

In general, F# quotations allow us to treat F# code as data structure and manipulate with it. This is very similar to C# expression trees, but the F# implementation is more powerful. We can also mark a standard method or a function with a special attribute that tells the compiler to store quotation of the body. Then we can access the quotation and traverse it or modify it. In this article we'll use a function that takes an F# quotation (containing a limited set of functions) and executes it using MSR Accelerator. Implementing this functionality is a bit complicated, so we won't discuss the implementation now. We'll leave this for some future article of this series. In future, we'll also look at other interesting possibilities that we have when writing code using quotations. Here is a list of articles in this series and of the articles that I'm planning to add:

• Accelerator and F# (I.): Introduction and calculating PI
• Accelerator and F# (II.): The Game of Life on GPU
• Accelerator and F# (III.): Data-parallel programs using F# quotations
• Accelerator and F# (IV.): Composing computations with quotations

Accelerator and F# (II.): The Game of Life on GPU

In the previous article, I introduced the Microsoft Research Accelerator library. It allows us to write computations with arrays in C# and execute them in parallel on multi-core CPU or more interestingly, using GPU shaders. In the previous artcile, we've seen how Accelerator works and how it can be accessed from F#. In this article, we'll look at one more interesting F# demo - we'll implement the famous Conway's Game of Life [1] using Accelerator. We'll use a v2 version of Accelerator which has been announced just recently and is available from Microsoft Connect [2].

This article is the second one from a series about using Accelerator from F#. Today, we'll use Accelerator types directly from F# - this is the simplest possible approach and is very similar to the way you'd work with Accelerator in C#. However, we can use some nice F# features such as custom operators to make the code more readable. In the next article, we'll discuss a different approach - we'll look how to execute more "standard" F# code (that doesn't reference Accelerator explicitly) with Accelerator using F# quotations. The list of articles may change, but here is a list of articles that I'm currently planning to write:

• Accelerator and F# (I.): Introduction and calculating PI
• Accelerator and F# (II.): The Game of Life on GPU
• Accelerator and F# (III.): Data-parallel programs using F# quotations
• Accelerator and F# (IV.): Composing computations with quotations

Accelerator and F# (I.): Introduction and calculating PI

I already wrote about two projects that I worked on during an internship at MSR back in 2007 (ASP.NET support in F# and F# WebTools). Even though this was more than 2 years ago (and I did one more internship at MSR in the meantime), I still have one more project that I never published on the web. The folks from the F# team reminded me of this project recently, so I thought I could finally publish it. The project used Microsoft Research Accelerator [1, 2], which is a C# library for developing array-based computations and executing them on a GPU. More recently, the Accelerator team at MSR published Accelerator v2 [3], which was a good motivation to update my original project...

In this article, we'll look at the simplest way of using Accelerator from F#. Accelerator provides a managed interface that can be naturally used from both C# and F#. We can use a mix of method calls and overloaded operators to describe a computation. In F#, we'll also define our additional custom operators to make the code a bit nicer. After we introduce Accelerator using a simple C# demo, we'll look how to calculate an approximate value of the PI number using a Monte-Carlo method.

This article is the first one from a series about using Accelerator from F#. The list of articles may change, but here is a list of articles that I'm currently planning to write:

• Accelerator and F# (I.): Introduction and calculating PI
• Accelerator and F# (II.): The Game of Life on GPU
• Accelerator and F# (III.): Data-parallel programs using F# quotations
• Accelerator and F# (IV.): Composing computations with quotations

Functional Programming in .NET using C# and F# (Manning Greenpaper)

Functional programming languages have been around for a while and were always astonishing for their ability to express the ideas in a succinct, declarative way allowing the developer to focus on the essence of problem rather than on technical details of the solution. Recently, functional paradigm is gaining new prominence as an efficient way to handle development of multi-processor, parallel and asynchronous applications.

Functional ideas are arising in C# as well as in other main-stream languages and functional languages are becoming an alternative for real-world projects. Also, Microsoft recently introduced a new language called F#, which has a strong background in traditional functional languages, but as a .NET language also benefits from the rich .NET and Visual Studio ecosystem.

Available via MEAP | 500 pages
Softbound print: March 2009 (est.)

This article is partially an excerpt from my book Real-world Functional Programming in .NET [1]. Thanks to my editors at Manning I have the permission to publish it on my blog. We’ll look at several aspects of functional programming and how the same concepts, which are essential for the functional paradigm, look in the F# and in C# 3.0 with LINQ. We will shortly look at the basic programming language features like lambda functions and type inference that are now available in both F# and C#. Functional programming isn’t only about language features, but also about using different programming style, so we’ll look at some high level concepts as well. These include using immutable data structures for developing code that can be executed in parallel and writing code in a more declarative style.

Thanks to the combination of C# 3.0 and F#, this article shows the ideas in a way that should be familiar to you in C#, but also shows a further step that you can take with a primarilly functional language F#. If you're a .NET developer and you want to understand what functional programming is and how it can help you to become better and more productive then continue reading. If you'll find this article interesting, then don't forget to check out the book, which explains everything in larger detail and discusses many other interesting ideas.

Reactive programming (I.) - First class events in F#

I believe that the LINQ project and changes in C# 3.0 and VB 9 are interesting because they allow rewriting of many ideas from functional programming. An ability to express queries easily is one of these ideas, but it is definitely not the only one. There are many other interesting ideas. The C# 3.0 language isn't primary a functional language, so it isn't easy to discover the idea if you use only C#, but it is possible to implement it if you know the idea already.

I already wrote a few interesting C# examples that were inspired by some functional idea. I'm a big fan of the F# language, so it is not a surprise that I started with an F# version of the problem and then looked at the way to do the same thing in C#. In particular, this is how my article about building dynamic queries in C# came to the existence - the F# version used FLINQ and Quotations and then I demonstrated how to do the same in C# using expression trees. Another example is my article about asynchronous programming in C# using iterators, which shows how to implement something like F# asynchronous workflows using iterators in C# 2.0.

Functional Reactive Programming

Today, I'm going to look at another very interesting idea from functional programming. It is called Functional Reactive Programming and it comes from the Haskell community. You can find a list of related Haskell projects here. However, similar things (though they are not purely functional and simplified) are available in the F# language as well. Don Syme introduced them in his blog post called F# First Class Events: Simplicity and Compositionality in Imperative Reactive Programming. In this article, I'm going to briefly introduce the implementation available in F# and I'll extend it a little bit to allow some more interesting things. In the second article from this series, I'll show how to implement the same thing in C# 3.0 (and in VB 9 too!)

Dynamic Lookup in F#

Many people view dynamic and statically-typed languages as two distinct groups (and this is often a reason for never-ending discussions). In this article, I'll try to show one interesting example, which demonstrates that these two groups are not in fact that distinct and that you can implement a common dynamic language feature in F#, which is undoubtedly statically-typed. The feature that I'm talking about is dynamic invoke using a symbolic representation of the member (this is something that can be done using symbols in Ruby, but I'll shortly explain what exactly I mean).

I intentionally wrote statically-typed and dynamic instead of dynamically-typed. In my understanding dynamic is a broader term while dynamically-typed and statically-typed are of course two distinct groups. On the other side dynamic refers to language features that are usually available in dynamically-typed languages, just because it is easy to support them in a nice way. This doesn't mean that having a dynamic feature in a statically-typed language would be impossible - it is just more difficult to implement it in a way that would be similarly elegant.

F# Overview (IV.) - Language Oriented Programming

In the fourth article of the F# overview series, I will shortly describe how I understad the language oriented paradigm and how the F# language can be used for developing libraries using this paradigm. We will look how discriminated unions relate to this paradigm and at three specific features that support this paradigm, namely active patterns, computation expressions and quotations.

Defining precisely what the term language oriented programming means in context of the F# language would be difficult, so I will instead explain a few examples that will demonstrate how I understand it. In general, the goal of language oriented programming is to develop a language that would be suitable for some (more specific) class of tasks and use this language for solving these tasks. Of course, developing a real programming language is extremely complex problem, so there are several ways for making it easier. As the most elementary example, you can look at XML files (with certain schema) as language that are processed by your program and solve some specific problem (for example configuring the application). As a side note, I should mention that I'm not particularly happy with the term ‘language’ in this context, because the term can be used for describing a wide range of techniques from very trivial constructs to a complex object-oriented class libraries, but I have not seen any better term for the class of techniques that I’m going to talk about.

F# Overview (I.) - Introduction

In my bachelor thesis I included a short introduction that covered all of the important aspects of the F# programming language and I thought that it may be useful to extend it a little bit to cover also a topics that were not important for my thesis and post it as an article, so there is one and relatively short article that introduces all the interesting F# features. The article got however a bit longer than I expected, so I decided to split it into a three parts that would introduce three different paradigms that are supported by F#. Of course, this series won't teach you everything about F#, but it tries to cover the main F# design goals and (hopefully) presents all the features that make F# interesting and worth learning. In this first part I will shortly introduce F# and the supported paradigms that will be discussed in the upcoming articles.

F# Quotations Samples on CodePlex

Some time ago, Granville Barnett (see his homepage and old blog [^] or a new blog [^]) had a great idea and started a CodePlex project called F# Samples [^] to host various samples written in F# to demonstrate the most important concepts of both functional programming and F#. I quite like this idea, so I asked Granville if I could join and add some samples that I wrote and today I finally found a time to update what I wanted to upload to the latest version of F# and put it online.

Building LINQ Queries at Runtime in F#

In an article about building LINQ queries at runtime in C# 3.0, I described how you can build a LINQ query dynamically, for example by combining a set of conditions using the 'or' operator in the where clause. I mentioned that the way I implemented it is largely influenced by the F# language, which provides very natural way for manipulations with code like this. In this article I will first shortly introduce FLINQ sample, which is an F# library implementing LINQ support and than I will implement the same examples I presented in the earlier article in F#.

Concepts behind the C# 3.0 language

One of the lectures that I attended last year was Programming Methodology and Philosophy of Programming Languages. The lecture was mostly about history of programming languages and how several features evolved, disappeared and than after many years appeared again in another programming language.

As I final work I decided to write an article that describes ideas that influenced the design of the C# 3.0 language. Some of these features are known from functional languages (for example from LISP or Haskell), some other were developed at Microsoft Research and appeared in the F# language or Cω. I also wanted to show in what ways are these features limited in the C# 3.0. I think that thanks to these limitation, the C# 3.0 is still a simple (or at least not difficult) to understand which is very important for mainstream language, but I find it interesting to know what is possible in other (less limited) languages.

• You can also download the article in PDF (404kB)
• The article is also available at CodeProject.com

F# metaprogramming and classes

F# quotations allows you to easily write programs that manipulate with data representation of program source code. If you're not familiar with quotations I recommend reading my previous article [1] that contains short introduction to this topic first. Quotations can be used for example for translating subset of the F# language to another code representation or another language.

To get the quotation data of the expression you can either use <@@ .. @@> operator or resolveTopDef function. In the first case the code written between the "<@@" and "@@>" is converted to data during the compilation. The resolveTopDef function allows you to get quotation data of top-level definition (function) from compiled library at runtime (you have to use --quotation-data command line switch while compiling the library). I mentioned that quotations can be used to represent only subset of the F# language. Currently, one of the quotation limitations is that it's not possible to enclose the whole class in the quotation operators. It is also not possible to get the representation of the whole class at runtime nor the representation of class members (for example methods).

In this article I'll present a simple method that makes it possible to use F# quotations for working with classes as well, however this is rather a prototype that can be used for experimenting and discovering areas where working with classes might be useful, not a fully working solution.

F# quotations visualizer - reloaded!

Some time ago, I wrote an article about useful utility called F# quotations visualizer. This utility can be used to show visual representation of F# quotations, that can represent (subset of) source code written in F#. There are two ways that you can use to get F# quotations - first is using operators <@@@@ ... @@@@> (this returns quotation of the code written inside the operator), second method is to get quotation of top level definition from compiled F# assembly (you have to explicitly enable this using command line switch --enable-quotation-data while compiling assembly).

Because I added several new features to the original Quotations visualizer, I decided to publish the latest version - here is the list of main improvements:

• Rewritten using active patterns (new F# language feature)
• It is possible to extract quotations from compiled F# assembly (if it contains quotation data)
• Added support for several missing language constructs

F# quotations visualizer

I already explained what F# quotations are and I explained how you can do some simple manipulations with it. In this article I'd like to present an application that I wrote and that can be helpful when working with quotations. It displays clear graphical representation of given F# quotation (using Windows Forms TreeView control).

F# - Simple quotations transformation

This article describes very simple code that I wrote while learning how to work with the F# quotations library. Using the F# quotations you can get tree representation of the quoted expression. This allows you to write code that takes code written in F# as data and performs some code analysis or compiles/translates that code to different language. This is very similar to the new C# 3.0 expression trees where you can get expression tree from lambda expression and translate this tree for example to SQL (using DLINQ). However expression trees in C# 3.0 are very limited when compared with F# quotations, so that's one of the many reasons why F# is interesting language.

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