ARCS 2027

ARCS 2027 : Unconventional Computing, Beyond von Neumann Computing
Magdeburg, Germany
March 9 -11 2027

The ARCS conferences series has a 40-year tradition on reporting leading-edge research in computer architectures and operating systems. Modern workloads particularly AI/ML and Big Data processing, manipulate enormous amounts of data. As data movement increasingly dominates system design,
conventional von Neumann architectures face fundamental constraints in performance, efficiency, and sustainability. The focus of the ARCS’27 conference will be on unconventional computing covering computer architectures and computing paradigms that explore alternative ways of representing, storing, and processing information

In addition to the main conference, ARCS will host:

• A special track on Organic Computing.
• A special track on Dependability and Fault Tolerance.
• A PhD forum to present the work of early-stage doctoral students.
• A Group forum for new professors, individual researchers, and consortia to present their research.

The proceedings of ARCS 2027 will be published in the Springer Lecture Notes on Computer Science (LNCS) series.

Topics of Interest

• Hardware Architectures: Reconfigurable architectures, Domain-specific accelerator architectures, RISC-V and open-source architectures, AI accelerators
• rogramming Models and Runtime Environments: Programming models for heterogeneous computing, Operating systems, algorithms, and data structures for heterogeneous architectures, System management including but not limited to scheduling, memory management, power/thermal management, and RTOS
• Cross-sectional Topics: Near- and in-memory computing, Memory and network compression, Organic computing, Pervasive systems

Submission guidelines: https://arcs-conference.org/submission-guidelines.

Organizers
General Co-Chairs: Thilo Pionteck, Otto von Guericke (University Magdeburg, Germany), Sven Tomforde (Christian-Alberts University Kiel, Germany)
PC Co-Chairs: Martin Kumm (University of Applied Science Fulda, Germany), Stefan Wildermann (Friedrich-Alexander-Universität Erlangen-Nürnberg)