The ARCS conferences series has a 40-year tradition on reporting leading-edge research in computer architectures and operating systems. This year, the conference has a special focus on: "Unconventional Computing: Beyond von Neumann Computing".

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. By relaxing the strict separation of memory and computation, and by exploiting physical phenomena or the intrinsic properties of emerging materials, approaches such as neuromorphic, quantum, reconfigurable, and in-memory computing open alternative approaches to efficient and scalable information processing. We welcome all contributions on hardware architectures (including extensions to classic approaches), operating systems, design tools, as well as programming models, algorithms, and data structures that advance computing efficiency—from von Neumann and beyond.

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 Research Group forum for early-career professors, researchers, and consortia to present their research

• Hardware Architectures
  • Reconfigurable architectures

  • Domain-specific accelerator architectures

  • RISC-V and open-source architectures

  • AI accelerators

  • System-on-chip

  • Parallel and distributed systems

  • High-performance systems

  • Heterogeneous many-core architectures

  • Real-time and mixed-criticality systems

  • I/O and non-volatile memory

  • Energy-efficient architectures

  • Smart network technologies

  • Dependable and fault-tolerant architectures


• Programming 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

  • Tools for power monitoring and performance analysis

  • Hypervisors and middleware for homogeneous and heterogeneous multi-/many-core computing platforms

  • Domain-specific languages and programming models

  • Architecture-specific code generation and optimization

  • Architectural simulation and emulation

• Cross-sectional Topics
  • Near- and in-memory computing

  • Memory and network compression

  • Organic computing

  • Pervasive systems

  • Autonomous systems

  • Application-specific arithmetic
  • Approximate computing

  • Hardware security
  • Safety

  • Hardware in the loop

  • Optimization and performance analysis

All submission details incl. the page length and deadlines can be found in the Submission Guidelines.