Gibbon is an experimental compiler that transforms high-level functional programs to operate on serialized data.
Typically, programs that process tree-like data represent trees using pointer-based data structures in memory (one heap object per-leaf and per-node) because such a layout is convenient to manipulate in a high-level programming language. This is also generally distinct from the representation of the data in serialized form on disk, which means that a program must perform some sort or marshaling when working with serialized data. Gibbon unifies the in-memory and serialized formats, transforming recursive functions to operate directly on serialized data.
Additionally, while the pointer-based structure is efficient for random access and shape-changing modifications, it can be inefficient for traversals that process most or all of a tree in bulk. The Gibbon project aims to explore optimizations of recursive tree transforms by changing how trees are stored in memory.
Currently, the Gibbon compiler has multiple front-ends: an s-expression synax similar to Typed Racket, and a small subset of Haskell.
Build the compiler with:
$ git clone https://github.com/iu-parfunc/gibbon && cd gibbon/gibbon-compiler $ stack setup && stack build
Run a sample program from the examples directory:
$ stack exec -- gibbon -r ./demo/Add1.hs
For more options:
$ stack exec -- gibbon -h
|ECOOP'17|| Compiling Tree Transforms to Operate on Packed Representations:
Michael Vollmer, Sarah Spall, Buddhika Chamith, Laith Sakka, Chaitanya Koparkar, Milind Kulkarni, Sam Tobin-Hochstadt, Ryan Newton [PDF]
|PLDI'19|| LoCal: A Language for Programs Operating on Serialized Data:
Michael Vollmer, Chaitanya Koparkar, Mike Rainey, Laith Sakka, Milind Kulkarni, Ryan R. Newton [PDF]
|ICFP'21|| Efficient Tree-Traversals: Reconciling Parallelism and Dense Data Representations:
Chaitanya Koparkar, Mike Rainey, Michael Vollmer, Milind Kulkarni, Ryan R. Newton [PDF]