Lobster is a GPU-accelerated framework for neurosymbolic programming that combines deep learning with symbolic reasoning.
Lobster maps a neurosymbolic language based on Datalog to the GPU programming paradigm via compilation to an intermediate language called APM.
This enables Lobster to be both flexible, supporting different modes of reasoning, and performant, implementing new optimization passes.
Lobster achieves an average speedup of 5.3x over Scallop, a state-of-the-art neurosymbolic framework, and enables scaling of neurosymbolic solutions to previously infeasible tasks.