A high-level interface to the operations in the core language (Feldspar.Core). Many of the functions defined here are imitations of Haskell's list operations, and to a first approximation they behave accordingly.

A symbolic vector (Vector) can be thought of as a representation of a parallel core array. This view is made precise by the function freezeVector, which converts a symbolic vector to a core vector using parallel.

Vector is instantiated under the Computable class, which means that symbolic vectors can be used quite seamlessly with the interface in Feldspar.Core.

Unlike core arrays vectors don't use any physical memory. All operations on vectors are "fused" which means that intermediate vectors are removed. As an example, the following function uses only constant space despite using two intermediate vectors of length n.

 sumSq n = sum (map (^2) (1...n))

Memory is only introduced when a vector is explicitly written to memory using the function memorize or converted to a core array using freezeVector. The function vector for creating a vector also allocates memory.

Note also that most operations only introduce a small constant overhead on the vector. The exceptions are

• dropWhile
• fold
• fold1
• Functions that introduce storage (see above)
• "Folding" functions: sum, maximum, etc.

These functions introduce overhead that is linear in the length of the vector.

Finally, note that freezeVector can be introduced implicitly by functions overloaded by the Computable class. This means that, for example, printCore f, where f :: Vector (Data Int) -> Vector (Data Int), will introduce storage for the input and output of f.