27. – 30. August 2017, Dagstuhl Seminar 17352

Analysis and Synthesis of Floating-point Programs


Eva Darulova (MPI-SWS – Saarbrücken, DE)
Alastair F. Donaldson (Imperial College London, GB)
Zvonimir Rakamaric (University of Utah – Salt Lake City, US)
Cindy Rubio-Gonzalez (University of California – Davis, US)

Auskunft zu diesem Dagstuhl Seminar erteilen

Annette Beyer zu administrativen Fragen

Roswitha Bardohl zu wissenschaftlichen Fragen


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Nowadays, floating-point computation is supported on a wide range of computing platforms, ranging from smartphones and embedded devices all the way to supercomputers. However, writing correct, yet high-performance and energy-efficient flfloating-point software is a challenging and complex task that often requires high levels of expertise. This is in large part due to the non-intuitive nature of floatingpoint arithmetic: roundoff error means that many algebraic laws of the real numbers do not hold in the flfloating-point setting. There is a dire need to empower developers with automated techniques and tools for analysis and synthesis of floating-point programs.

Research related to floating-point computation spans a multitude of areas of computer science, ranging from hardware design and architecture, all the way to high-performance computing, machine learning, and software analysis and verification. The focus of this Dagstuhl Seminar is to connect researchers from these areas, with the goals of fostering collaboration, and brainstorming new theoretical advances, practical techniques and tools to improve the reliability and performance of floating-point computation.

There has been a lot of recent interest in floating-point optimization and reasoning, including expression rewriting and instruction generation to improve precision; abstract interpretation, automated theorem proving, SMT solving and global optimization for rigorous reasoning; and integration of lower-precision computations into floating-point programs to conserve energy while achieving acceptably stable results (important in high-performance computing and machine learning).

While these above approaches and techniques have certainly advanced the current state-of-the-art, they still suffer from various drawbacks, such as limited automation, precision, or scalability, which prevents them from being transferred into practical solutions. Much more work is needed, including breakthroughs that include completely novel techniques as well as novel combinations of existing methods.

The goal of this Dagstuhl Seminar is for the attendees to present their current research in the area of analysis, synthesis, and implementation of floating-point computations to their colleagues, many of whom will come from other areas of computer science. This will foster subsequent discussions and brainstorming sessions, with the ultimate goal in mind for ideas to ow from one area into another, for new collaborations to be established, and to lay groundwork for novel research directions.

  Creative Commons BY 3.0 DE
  Eva Darulova and Alastair F. Donaldson and Zvonimir Rakamaric and Cindy Rubio-Gonzalez


  • Programming Languages / Compiler
  • Semantics / Formal Methods
  • Verification / Logic


  • Floating-point arithmetic
  • Program optimization
  • Rigorous compilation
  • Precision allocation
  • Energy-efficient Computing


Bücher der Teilnehmer 

Buchausstellung im Erdgeschoss der Bibliothek

(nur in der Veranstaltungswoche).


In der Reihe Dagstuhl Reports werden alle Dagstuhl-Seminare und Dagstuhl-Perspektiven-Workshops dokumentiert. Die Organisatoren stellen zusammen mit dem Collector des Seminars einen Bericht zusammen, der die Beiträge der Autoren zusammenfasst und um eine Zusammenfassung ergänzt.


Download Übersichtsflyer (PDF).


Es besteht weiterhin die Möglichkeit, eine umfassende Kollektion begutachteter Arbeiten in der Reihe Dagstuhl Follow-Ups zu publizieren.

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