Yury Shikunov, Yury Stepchenkov, Dmitry Khilko, Dmitry Shikunov. Data redundancy problems in data-flow computing and solutions implemented on the recurrent architecture // 2017 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus) St. Petersburg, Russia, 1-3 Feb., 2017. — IEEE, P. 335 — 338. (indexed in Scopus).
DOI: 10.1109/EIConRus.2017.7910559

Abstract: This paper covers one of the main disadvantages of data-flow computational model — high overhead costs associated with storing and processing large volumes of tag data. Overcoming this disadvantage using various ways of data compression comes with a number of problems described in this article. To solve given problems new recurrent data-flow computational model was created as well as architecture based on that model. This paper describes key features and mechanics of the new model and architecture allowing us to reduce data redundancy in memory storage. Efficiency of developed mechanics is shown in implementation of fast Fourier transform algorithm.

Дополнительную информацию о содержании доклада вы можете получить на сайте конференции / You can get additional information on the content of the article on the conference website. Также вы можете связаться с авторами доклада, или с руководителем научной группы Степченковым Ю. А. ia_ste@mail.ru / You can also contact the authors of the report, or with the head of the scientific group Stepchenkov Ya. A. ia_ste@mail.ru.

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