Tobias Grosser
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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

Anastasiia

Anastasiia
Ruzhanskaia

Ph.D.
with Timothy Roscoe

Arjun

Arjun
Pitchanathan

Ph.D.
from Jan 2021

Lorenzo

Lorenzo
Chelini

Ph.D.
with Henk Corporaal

Mathieu

Mathieu
Fehr

Ph.D.
from Mar 2021

Siddharth

Siddharth
Bhat

Ph.D.
from Jan 2021

Theodoros

Theodoros
Theodoridis

Ph.D.
with Zhendong Su

You

You

Ph.D.
Would you enjoy research?

Tobias

Tobias
Gysi

Postdoctoral Researcher
 

Previous Members

  • Christoph Mueller, Researcher

    2020
    Moved toMeteoSwiss
    Scientific Software Developer

  • 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