### In a Nutshell

LambdaCube 3D is a domain specific language and library that makes it possible to program GPUs in a purely functional style.

Purely Functional Rendering Engine

April 28, 2013

Posted by on We are in the process of creating the next iteration of LambdaCube, where we finally depart from the Haskell EDSL approach and turn the language into a proper DSL. The reasons behind this move were outlined in an earlier post. However, we still use the EDSL as a testing ground while designing the type system, since GHC comes with a rich set of features available for immediate use. The topic of today’s instalment is our recent experiment to make illegal types unrepresentable through a custom kind system. This is made possible by the fact that GHC recently introduced support for promoting datatypes to kinds.

Even though the relevant **DataKinds** extension is over a year old (although it’s been officially supported only since GHC 7.6), we couldn’t find any example to use it for modelling a real-life domain. Our first limited impression is that this is a direction worth pursuing.

It might sound surprising that this idea was already brought up in the context of computer graphics in the Spark project. Tim Foley’s dissertation briefly discusses the type theory behind Spark (see Chapter 5 for details). The basic idea is that we can introduce a separate kind called **Frequency** (Spark refers to this concept as **RecordType**), and constrain the **Exp** type constructor (**@** in Spark) to take a type of this kind as its first argument.

To define the new kind, all we need to do is write a plain data declaration, as opposed to the four empty data declarations we used to have:

data Frequency = Obj | V | G | F

As we enable the DataKinds extension, this definition automatically creates a kind and four types of this kind. Now we can change the definition of **Exp** to take advantage of it:

data Exp :: Frequency -> * -> * where ...

For the time being, we diverge from the Spark model. The difference is that the resulting type has kind ***** in our case, while in the context of Spark it would be labelled as **RateQualifiedType**. Unfortunately, Haskell doesn’t allow using non-* return kinds in data declarations, so we can’t test this idea with the current version. Since having a separate **Exp** universe is potentially useful, we might adopt the notion for the DSL proper.

We don’t have to stop here. There are a few more areas where we can sensibly constrain the possible types. For instance, primitive and fragment streams as well as framebuffers in LambdaCube have a type parameter that identifies the layer count, i.e. the number of framebuffer layers we can emit primitives to using geometry shaders. Instead of rolling a custom solution, now we can use type level naturals with support for numeric literals. Among others, the definition of stream types and images reflects the new structure:

data VertexStream prim t data PrimitiveStream prim (layerCount :: Nat) (stage :: Frequency) t data FragmentStream (layerCount :: Nat) t data Image (layerCount :: Nat) t where ...

Playing with kinds led to a little surprise when we looked into the texture subsystem. We had marker types called **DIM1**, **DIM2**, and **DIM3**, which were used for two purposes: to denote the dimension of primitive vectors and also the shape of equilateral textures. Both structures have distinct fourth options: 4-dimension vectors and rectangle-shaped textures. While they are related – e.g. the texture shape implies the dimension of vectors used to address texels –, these are different concepts, and we consider it an abuse of the type system to let them share some cases. Now vector dimensions are represented as type-level naturals, and the **TextureShape** kind is used to classify the phantom types denoting the different options for texture shapes. It’s exactly like moving from an untyped language to a typed one.

But what did we achieve in the end? It looks like we could express the very same constraints with good old type classes. One crucial difference is that kinds defined as promoted data types are closed. Since LambdaCube tries to model a closed domain, we see this as an advantage. It also feels conceptually and notationally cleaner to express simple membership constraints with kinds than by shoving them in the context. However, the final decision about whether to use this approach has to wait until we have the DSL working.

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