Call for Papers

Motivation

The design of Real-Time and Embedded Systems is, by definition, subject to constraints:

  • timing of the input, output, or both;
  • minimal quality of the delivered output/service;
  • limited energy, power, or processing/communication resources, and more.

The design space exploration is often driven by expert designers who make the design decisions based on their experience. Such a design phase, however, can be more systematically modeled as an optimization problem, as long as the goal of the design becomes a cost to be minimized. This enables the usage of standard solvers of optimization problems.
The complexity of such a phase, however, is affected by several dimensions, including:

  • the size of the problem (e.g. the sample automotive application of the WATERS 2017 challenge composed by ~1000 functions and ~10000 shared variables);
  • the accuracy of the model for the workload and the computing platform;
  • the tolerable degree of approximation of the constraints.

Fundamentally, the nature of the design problem as described above never changed over time. Today, however, the rise of ML/AI methods as universal tools to solve optimization problems (and any other problem) without any guarantee on the quality of the solution, is challenging the sound practice of addressing the design phase with optimization.

This workshop aims at being a venue in which researchers from the academia and industry working on real-time constraints, design-space exploration, complexity and optimization, meet to share ideas, problems, and solutions.

Topics of Interest

Topics of interest include, but are not limited to:

  • Optimization variables:
    • parameters of tasks (period, execution times, etc.);
    • amount of processing and communication capacity (speed/bandwidth);
    • heterogeneous computing: type/quantity of accelerators (GPU, FPGA elements, etc).
  • Model of the cost of design:
    • borrowed from different application contexts: automotive, avionics, data centers, mobile devices, edge;
    • maximum extensibility of functionalities;
    • maximum battery savings and lifetime.
  • Model of the constraints:
    • schedulability constraints;
    • sensitivity analysis;
    • deadline model: hard/soft/probabilistic constraints;
    • accurate vs. efficient representation of constraints: approximations.
  • Solvers:
    • continuous vs. discrete methods (granularity of discretization);
    • gradient-descent, linear programming (LP), quadratic programming;
    • mixed-integer linear programming (MILP);
    • constraint programming (CP);
    • meta-heuristics: simulated annealing, tabu search, genetic algorithms;
    • efficient problem formulations.

Type of submissions

This workshop seeks a diversified program bridging established results with recent challenges. For this reason, we welcome different types of contributions.

  • Original contributions.
  • Preliminary ideas, not necessarily mature, seeking for feedback from the community.
  • Short versions of previously published research, relevant to the field.

To encourage submissions, the format of accepted submissions is very lightweight and permissive: from two pages in double column format and up with a flexible page limit (do discuss beforehand with the workshop chair if you plan on submitting eight or more pages.)

Publication of the workshop material

Accepted papers will be informally published on the workshop webpage. Authors will retain the copyright of their submitted material, and are free to submit it elsewhere.

Important Dates

Deadline for contributions (firm): September 22nd, 2024
Notification (tentative): October 8th, 2024
Camera-ready deadline (tentative): October 15th, 2024
The OPERA Workshop: December 10th, 2024

Submit Here