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News
August 13, 2026
‘Working with AI Solves a Wide Range of Engineering Problems
Artificial intelligence is a working tool based on a balanced combination of algorithms and engineering. Experts and doctoral students from the HSE Moscow Institute of Electronics and Mathematics explain how AI technologies can improve an application, device, or system, and what engineering tasks are solved in the process.
August 12, 2026
‘I Would Like My Research to Help Make the World a Calmer and Better Place
Whatever task Saraa Ali, Junior Research Fellow at the Laboratory of Methods for Big Data Analysis (LAMBDA) of the AI and Digital Science Institute (HSE Faculty of Computer Science), is working on, she thinks about how it can benefit people. She told the Young Scientists of HSE University project about her large family, diagnosing three-phase motors, and her dream of building a children’s home in her native country.
August 11, 2026
‘The Peak of Stupidity and ‘The Valley of Despair: HSE Economists Propose an Explanation for the Dunning–Kruger Effect
The Dunning–Kruger effect, which describes a sharp surge in self-confidence among beginners followed by an equally rapid decline as they gain experience, can be explained by the nature of the learning process and the acquisition of new knowledge. This conclusion was reached by Andrey Vorchik of the HSE Faculty of Economic Sciences together with independent researcher Murat Mamyshev. They developed a mathematical model of learning and demonstrated how subjective confidence is formed and changes as knowledge accumulates, as well as how teachers can reduce the ‘valley of despair’ experienced by learners.

 

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Routing Algorithms in Optimal Degree Four Circulant Networks Based on Relative Addressing: Comparative Analysis for Networks-on-Chip

IEEE Transactions on Network Science and Engineering. 2023. Vol. 10. No. 1. P. 413–425.
Monakhova E. A., Monakhov O. G., Romanov A.

The solution of the problem of organizing optimal communications in circulant networks of degree four is considered. For a family of optimal circulant networks with the minimum diameter and average distance for any number of nodes in a graph, we propose an optimal pair routing algorithm of constant complexity based on using the relative addressing of nodes in a network. The new algorithm is an analytical extension to any number of nodes in the network of the routing method proposed for dense Gaussian networks, and it does not use division operations, which are very expensive to implement in fixed-point format. This extension is based on the proposed scheme of transformations on the plane of geometrical patterns of optimal circulant networks. The developed routing algorithm is the basis for generating the series of routing algorithms for different subfamilies of the optimal two-dimensional circulants. The general routing algorithm and its modification for a separate subclass of circulants are implemented in the HDL NoC model with circulant topology. All the algorithm parameters important for networks-on-chip, including the consumption of memory, logical resources, and execution time are comprehensively investigated. The results of a comparative analysis of the new algorithms with other routing algorithms, previously implemented in the networks-on-chip, are presented.

Research target: Electronics and Electrical Engineering Computer Science
Language: English
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Keywords: routingnetwork-on-chipcirculant topology
Publication based on the results of:
Automation of networks-on-chip modeling (2023)
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