Tobias Grosser

Tobias Grosser

Reader in Compilers and Runtime Systems

University of Edinburgh


My interests are compilation, programming language design, and effective performance programming. However, I define these areas broadly. As a result, I ask questions such as:

  • How can compilers contribute to understanding climate change?
  • Can machine learning help us to automate compiler design and performance programming?
  • Can compilers revolutionize how hardware (ASICs, CPUs, ...) is designed?
  • Can formal verification increase confidence in self-driving cars?
  • How can performance programming become a smooth and interactive experience for developers?
Check out my research vision for details!

In my research, I aim to:

  • address problems important to society,
  • advocate for diversity,
  • work with the open-source community,
  • show that well-being increases scientific performance.

I previously have been affiliated with:

Join
NEWS: I just moved to Edinburgh and am building a new group. Hence, I am planning to take several Ph.D. students and postdoctoral researchers over the next year. Get in touch!

Are you considering a PhD? I really enjoy working with students! There is nothing more rewarding for me as a scientist than seeing a student develop and execute their very personal research vision. I am excited to provide you guidance along this path.

Explore my research vision, papers, and projects. If a topic catches your attention or you want to discuss your personal research idea, email me.

I also regularly host postdoctoral researchers and interns.

Team

Previous Members

  • Jakub Lichman, M.Sc. Thesis

    2020
    Moved toGoogle
    Internship with Albert Cohen and Oleksandr Zinenko

  • Theodoros Theodoridis, Researcher

    2019 - 2020
    Moved toETH Zurich
    Ph.D. student with Zhendong Su

  • Arjun Pitchanathan, Intern (M.Sc.)

    2019 - 2020
    Moved toUniversity of Edinburgh
    Ph.D. with me

  • Jean-Michel Gorius, Intern (M.Sc.)

    2019
    Moved toUniversity of Murcia
    Internship with Alexandra Jimborean

  • Mathieu Fehr, Intern (M.Sc.)

    2019
    Moved toMIT CSAIL
    Internship with Adam Chlipala

  • Anastiasiia Ruzhanskaia, Intern (M.Sc.)

    2018
    Moved toETH Zurich
    Ph.D. student with Timothy Roscoe

Publications

Google Scholar
Research Vision


Effective Performance Programming
by Re-Connecting Developers and Compilers

My research uses strong theoretical reasoning to bring innovations to real-world compilation and programming language problems. My current objective is to rethink performance programming by re-connecting developers and compilers. Today, performance programming is no longer limited to the optimization of low-level code but often includes the use of domain-specific compilers, constraint programming libraries, complex performance models, and automatic (potentially learned) strategies to search for optimal code transformations.

My primary objectives are:
  • making compilation more modular, predictable, automatic, and trustworthy
  • bringing open-source compiler innovation to an increasingly broad set of targets from GPUs over FPGAs to custom hardware, and
  • breaking down the barriers between compilers and programmers by enabling their interaction via the programming language environment.

I dream of a future where performance programming is an intuitive play between the programmer and the compiler. A game that smoothly moves between manual as well as automatic techniques and works across software and hardware.

I am particularly interested in the following areas:
  • Compilers
  • Static & dynamic analysis
    • Abstract interpretation based program analysis
    • Performance and cache models
    • Test case generation
  • Human-compiler interface
  • Domain-specific compilation
    • Deep learning
    • Climate science
  • High-performance computing
    • Loop optimization & polyhedral compilation
    • Vectorization
  • Compilation for accelerators: GPU, FPGA
  • Open-source hardware
    • Compiler support for RISC-V
    • Software/hardware co-design
  • SMT and constraint solving
    • Mixed integer linear programming
    • SAT solving
    • Parametric counting using Barvinok’s algorithm
  • Automatic theorem proving for compiler verification and constraint solving
  • Effective compilation from functional languages to imperative code
  • Artificial intelligence for compilers and constraint solvers

Contact
Tobias Grosser

School of Informatics
10 Crichton Street
Room: 1.04
Edinburgh EH8 9AB, United Kingdom

first.last at ed.ac.uk