Slides.

This is a new golden age for optimizing compilers. We live in a heterogeneous world of domain-specific languages and accelerators, freeing programming language and computer architects from the chains of general-purpose, one-size-fits all designs. [John Hennessy and Dave Patterson’s Turing award lecture, shamelessly adapted.] The emphasis moves from abstraction penalty removal to zero-cost abstraction by design, from optimization targeting a von Neumann architecture to the orchestration of a distributed hierarchy of computational and memory resources, from performance through native libraries to just-in-time code generation in active libraries, from expert-written heuristics to machine learning compilation and program synthesis. Beyond performance, compiler construction for heterogeneity also raises challenges in debuggability across abstractions and languages, and compilation for security. Building on applications from high performance computing, machine learning and security, we will illustrate these challenges on the design of MLIR, a new open source infrastructure to accelerate innovation in machine learning (ML) and high-performance computing (HPC). MLIR is built for extension and evolution, enabling research and engineering on heterogeneous compilation; it is also a research artifact raising its own design, semantics and algorithmic challenges.

Albert is a research scientist at Google. He has been a research scientist at Inria from 2000 to 2018. He graduated from École Normale Supérieure de Lyon and received his PhD from the University of Versailles in 1999 (awarded two national prizes). He has been a visiting scholar at the University of Illinois, an invited professor at Philips Research, and a visiting scientist at Facebook Artificial Intelligence Research. Albert Cohen works on parallelizing and optimizing compilers, parallel programming languages and systems and synchronous programming for reactive control systems. He served as the general or program chair of major conferences, including PLDI, PPoPP, HiPEAC, CC, the embedded software track of DAC, and as a member of the editorial board of ACM TACO and IJPP. He coauthored more than 180 peer-reviewed papers and has been the advisor for 26 PhD theses. Several research projects initiated by Albert Cohen resulted in effective transfer to production compilers and programming environments in industry.