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Computing Journal SI 2021 : Recent Advances in Autonomous Vehicle Solutions in the Digital Continuum

Submission Deadline: Sep 01, 2020
Notification of Acceptance: Nov 01, 2020
Camera Ready Version Due : Feb 01, 2021


The domain of autonomous vehicle computing systems is changing rapidly under the pressure of an intense competition, the continuous emergence of new markets and players. Research and development in autonomous vehicles poses many challenges and opportunities both in hardware and software across the Digital Continuum: from sensors at the Edge to HPC resources in the Cloud. Hardware requirements range from specific processor architectures, efficient SIMD processing on graphics processors, and efficient memory hierarchy. Similarly, software requirements range from operating system support and specialized image processing kernels, to efficient deep learning algorithms for scene and object detection. Special attention is paid to power limitations, cost for mass production, and safety.

Call For Paper

This special issue of Computing addresses recent advances for autonomous vehicles in the Digital Continuum encompassing the Edge, Fog, and Cloud Computing. Topics of interest include, but are not limited to:

  • Workload characterization and benchmarks for autonomous vehicles to be used in heterogeneous platforms.
  • Special accelerator architectures and microarchitectures to be used on the Edge.
  • Resource allocation approaches for autonomous vehicle computation needs.
  • Scheduling heuristics and run time environment solutions to achieve better throughput in computing systems with different constraints.
  • Framework and prototype experiences with integration of specialized components.
  • Testbed implementations with heterogeneous computing resources for autonomous vehicles.
  • Memory system design for specialized hardware.
  • System impact of offloading computation including interconnect technology, bandwidth, and data processing.
  • Programmability of heterogeneous hardware resources with variable distances.
  • Techniques to facilitate configurability or configurable solutions.
  • System evaluation and analysis of specialized platforms.

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