ABSTRACTS OF ARTICLES OF THE JOURNAL "INFORMATION TECHNOLOGIES".
No. 12. Vol. 31. 2025

DOI: 10.17587/it.31.649-658

S. G. Bobkov, PhD, Professor, Deputy Head of the Department, D. N. Zmejev, Researcher, A. V. Klimov, Senior Researcher, N. N. Levchenko, PhD, Leading Researcher, Department for Design Problems in Microelectronics of the Center for Advanced Microelectronics NRC,
"Kurchatov institute", Moscow, Russian Federation

Optimization of the Matching Process in Computing Systems Implementing a Dataflow Computing Model with a Dynamically Formed Context

Received on 31.05.2025
Accepted on 27.06.2025

The paper considers the problem of a drop in real performance with an increase in the number of computing cores on supercomputer systems. The results of the first three systems from the TOP500 List are analyzed. The main approaches to solving the problem of increasing real performance are given.
A dataflow computing model with a dynamically formed context is considered. The architecture of a parallel dataflow computing system implementing this model is described. The model and architecture are one of the approaches to improving the real performance of computing systems. The principles of functioning of hardware ternary content-addressable memory, which implements the dataflow computing model in the most efficient way, are described. This is due to the fact that the concept of the computing model, such as a token workspace, involves the simultaneous comparison of an incoming token with all tokens present in this space. One of the key problems of content-addressable memory is analyzed — high power consumption when performing matching operations. Methods for optimizing the matching process are proposed, which are divided into three groups — hardware, software, and hardware-software. Optimization methods are aimed at overall reducing the number of "parasitic" comparisons, as well as reducing the number of compared bits. An analysis of its effectiveness was carried out for each method. One of the effective methods of reducing the number of matchings in the content-addressable memory of the keys of the matching processor of the parallel dataflow computing system is the use of special "Double grouped" tokens. These tokens allow not only to reduce the total number of task tokens, but also to reduce the load on the communication network, reduce the number of comparisons, and free up execution units by transferring part of the load to the matching processor.
The research results obtained when performing various tasks on the behavioral block-register model of the system and the emulator are presented. The results demonstrate the effectiveness of the proposed methods.
Keywords: content-addressable memory, parallel dataflow computing system, dataflow computing model, matching process

P. 649-658

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