NURE Kharkiv national university of radioelectronics

Design Automation Department

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Modeling for Simulation (MOSI) Cloud Service

An in-memory intelligent vector-logic computing based on read-write transactions is proposed for the economical solution of digital project verification tasks according to the resource-saving metric – energy and time. The proposed mechanisms of in-memory MOdeling for SImulation nullify the complexity of data analysis algorithms due to the exponential redundancy of smart models. The results of this work are original and have been published in Scopus-indexed journals and conferences.

The Modeling for Simulation (MOSI) cloud service consists of the following components:

  1. synthesis of a testing map based on the logic vector of functionality;
  2. synthesis of a logic vector of a digital circuit defined by the logic vectors of its elements;
  3. simulation of the fault-free behavior of a logic circuit based on the vector representation of logic elements;
  4. fault simulation (as addresses) of logic circuits based on deductive vectors of logic elements;
  5. fault finding in logic functionality using its testing map;
  6. a GUI for logic circuit input, where elements are represented by logic vectors.

The relevance of creating the MOSI system as a cloud service lies in the economical solution of digital project verification tasks according to the resource-saving metric – energy (by at least 38%) and time (by at least an order of magnitude) – as well as in providing access to users from anywhere in the world, which serves as an example of future mass computing. More efficient use of resources, waste reduction, and minimizing the negative environmental impact contribute to preserving the planet’s ecology, which aligns with the Sustainable Development Goals (SDG 12 – Responsible Consumption and Production, SDG 9 – Industry, Innovation, and Infrastructure).

Authors:

  • Ivan Khakhanov, PhD (Candidate of Technical Sciences), Assistant at the APOT Department, NURE;
  • Georgiy Kulak, Assistant at the APOT Department, NURE;
  • Andriy Voronov, PhD Student at the APOT Department, NURE;
  • Oleh Demchenko, PhD Student at the APOT Department, NURE;
  • Nataliia Maksymova, PhD Student at the APOT Department, NURE;
  • Veronika Ponomarova, Engineer at the APOT Department, NURE.

Scientific Supervisor: Volodymyr Khakhanov, D.Sc., Professor at the APOT Department, NURE.