MLIR: A new intermediate representation and compiler framework

Posted by The TensorFlow MLIR Team The TensorFlow ecosystem contains a number of compilers and optimizers that operate at multiple levels of the software and hardware stack. As a day-to-day user of TensorFlow, this multi-level stack might manifest itself as hard-to-understand compiler and runtime errors when using different kinds of hardware (GPUs, TPUs, mobile). These components, starting from th

[rawwell]

“Dialects can define entirely custom types, which is how MLIR can model things like the LLVM IR type system (which has first class aggregates), domain abstractions important for ML-optimized accelerators like quantized types, and even the Swift or Clang type systems”