Objective
The energy consumption of data centers and ICT devices grows at an alarming rate and will be responsible for up to 20% of the global energy consumption by 2030. To sustain the ongoing digital transformation, we must find ways to run software dramatically more efficiently. A promising direction is incremental computing. Incremental computations react to input changes rather than recomputing their result from scratch, which is known to deliver asymptotic speedups in theory and order-of-magnitude speedups in practice.
However, current approaches to incrementality have limited applicability: They either require expert knowledge, or only support specialized domains (e.g. database queries), or only yield modest speedups. The goal of this project is to develop a methodology for automatically incrementalizing computations and significantly improving their time and energy efficiency.
The AutoInc project achieves this ambitious goal by establishing a novel foundation for incremental computing in three complementary parts:
- A library of incremental operators for atomic and other essential data types,
- A low-level intermediate representation (IR) for describing compositional incremental computations,
- An optimizing compiler that translates existing code to the low-level incremental IR.
Team
The PL Team from KIT.
Publications
Stateful Differential Operators for Incremental Computing. Runqing Xu and Sebastian Erdweg. Principles of Programming Languages (POPL). 2026
Incremental Computing by Differential Execution. Prashant Kumar, André Pacak, and Sebastian Erdweg. European Conference on Object-Oriented Programming (ECOOP). 2025
Mono types --- First-Class Containers for Datalog. Runqing Xu, David Klopp, and Sebastian Erdweg. European Conference on Object-Oriented Programming (ECOOP). 2025
A Typed Multi-level Datalog IR and Its Compiler Framework. David Klopp, Sebastian Erdweg, and André Pacak. Proceedings of the ACM on Programming Languages (OOPSLA). 2024
Object-Oriented Fixpoint Programming with Datalog. David Klopp, Sebastian Erdweg, and André Pacak. Proceedings of the ACM on Programming Languages (OOPSLA). 2024
Separate Compilation and Partial Linking: Modules for Datalog IR . David Klopp, André Pacak, and Sebastian Erdweg. Proceedings of Generative Programming: Concepts & Experiences (GPCE). 2024
Abstract Interpretation of Java Bytecode in Sturdy. Stefan Marx and Sebastian Erdweg. Proceedings of the 26th ACM International Workshop on Formal Techniques for Java-like Programs (FTfJP). 2024
This project is supported by ERC grant Asymptotic Speedups for Free through Automatic Incremental Computing
Last overhaul of this page: January 2026