SF Scala: Eugene Burmako & Alex Suhan, Swift as syntactic sugar for MLIR

ai.bythebay.io Nov 2025, Oakland, full-stack AI conference Scale By the Bay 2019 is held on November 13-15 in sunny Oakland, California, on the shores of Lake Merritt: https://scale.bythebay.io. Join us! ----- [Swift fo TensorFlow is covered in several talks at https://scale.bythebay.io, Bay Area, November 14-15, 2019.] Swift works great as an infinitely hackable syntactic interface to semantics that are defined by the compiler underneath it. The two options today are LLVM (there's a running joke that Swift is just syntactic sugar for LLVM) and TensorFlow graphs (which is the contribution of early versions of Swift for TensorFlow). Multi-Level Intermediate Representation (MLIR) is a generalization of both the LLVM IR and TensorFlow graphs to represent arbitrary computations at multiple levels of abstraction. This enables domain-specific optimizations and code generation (e.g. for CPUs, GPUs, TPUs, and other hardware targets). In the talk, we'll present some thoughts on how Swift could compile down to MLIR and show a few demos of prototype technologies that we've developed. Eugene Burmako (burmako@google.com) is working on Swift for TensorFlow at Google AI. Before joining Google, he made major contributions to Scala at EPFL and Twitter, founding Reasonable Scala compiler, Scalameta and Scala macros. Eugene loves compilers, and his mission is to change the world with compiler technology. Alex Suhan (asuhan@google.com) is also working on Swift for TensorFlow at Google AI. He has been using LLVM to accelerate machine learning and data analytics workloads for the last fi…