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"Algebraic data types and pattern matching are popular tools to build programs manipulating complex datastructures in a safe yet efficient manner  On top of its safety advantages  compilation techniques can turn pattern matching into highly efficient deconstruction code for immutable use cases  Conversely  high-performance datastructures and languages prefer to leverage  controlled  mutations to maximize time and memory efficiency  Algebraic data types provide a natural framework to efficiently describe  emph in-place  transformations as rewrite rules  Such representation coul take advantage of parallelism opportunities that appear in tree-like structures  We present early steps towards a new technique to compile pattern matching as parallel in-place modifications of the underlying memory representation  Towards this goal  we combine the usual language approach which is common in pattern-matching compilation with tools from the polyhedral model  which is commonly used in high-performance code generation to output efficient C code  We present our formalism  along with a prototype implementation "
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