Let's make compilers boring (again)!

Construction of equation-based modelling & simulation compilers

The integration between the physical and the digital world, as per the digital twin paradigm, requires experts from the physical world to model and to simulate increasingly large pieces of physical system in a digital system. Considering a general, multi-physical-domain model description, my research aims at re-defining the process of generating an exact simulation by improving the analyses, the transformations, and the intermediate representationsto bridge the gap between the current state-of-the-art and modern computer architectures.

Key technologies

• Source language: Modelica
• Tools: C++
• Frameworks: MLIR, LLVM

Compiler-based precision tuning

The trend towards the future of computation is not about computing faster, but rather about computing smarter. The key to the last digital revolution is to only compute what you need, and to reduce the size of the computational problem by reducing the number of bits used to represent each number. By allowing a fine-grained selection of how many bits each case study required to deliver an acceptable result, we can compute less and save time, energy, and hardware area. Most notably, AI applications are quite flexible in their definition of acceptable result, and they represent the main driver of this research field nowadays. In the last few years, a moltitude of options have been proposed as data types to compute less and save more, and the trade-off between fast and accurate is not anymore limited to a 0-1 selection. Which option to pick for which variable is a problem that should not fall on the shoulder of the programmer, and an automated tool like the compiler is exactly what the developers are looking for. The bad news is that we are not there just yet. The good news is that I know how to get there. Wanna jump on board?

Key technologies

• Source language: C/C++
• Tools: C++
• Frameworks: LLVM