The umbrella project DLVM introduces an end-to-end system from safe neural network DSLs to heterogeneous parallel code generation, demonstrating a new infrastructure for modern deep learning software.

DLVM Core is a design and implementation of a compiler infrastructure that consists of linear algebra operators, automatic differentiation, domain-specific optimizations and a code generator targeting heterogeneous parallel hardware. DLVM is designed to support the development of neural network DSLs, with both AOT and JIT compilation.

DLVM started as a research project at University of Illinois at Urbana-Champaign, and is now driven by a small community of researchers and developers. Most projects will be open-source later this year.


All projects are written in Swift.