CAD for Remote High-Level Modeling of NoC
Aleksandr Aleksandrovich AMERIKANOV,
Larisa Genadevna EVTUSHENKO,
Vladimir Victorovich ZUNIN,
Vladimir Maksimovich VINARSKII https://doi.org/10.15514/ISPRAS-2025-37(1)-8
Abstract
The paper is devoted to the description of the process of developing a new CAD architecture for high‑level modeling of NoC, as well as the remote flow of NoC design. The paper analyzes the main stages of NoC design and demonstrates the high importance of high-level modeling and its impact on the entire design process. Also, the possibility of conducting high-level modeling in a remote format using the client server architecture of the CAD is considered. The process of remote design of NoC using the proposed CAD system and remote testbed with FPGA debug boards is demonstrated.
Keywords
Supporting agencies: The publication was prepared within the framework of the Academic Fund Program at HSE University (grant № 24-00-012 Remote laboratory for working with embedded systems).
About the Authors
Aleksandr Aleksandrovich AMERIKANOV
HSE University
Russian Federation
Russian Federation
Cand. Sci (Tech.), Associate Professor at the HSE University. Research interests: CAD development, development of logic devices, FPGA, networks-on-chip.
Larisa Genadevna EVTUSHENKO
HSE University
Russian Federation
Russian Federation
Assistant lecturer at the HSE University. Research interests: development of logic devices, FPGA.
Vladimir Victorovich ZUNIN
HSE University
Russian Federation
Russian Federation
Senior Lecturer at the HSE University. Research interests: CAD development, development of logic devices, FPGA.
Vladimir Maksimovich VINARSKII
HSE University
Russian Federation
Russian Federation
Student at the HSE University. Research interests: SoC, FPGA, machine learning.
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Review
For citations:
AMERIKANOV A.A., EVTUSHENKO L.G., ZUNIN V.V., VINARSKII V.M. CAD for Remote High-Level Modeling of NoC. Proceedings of the Institute for System Programming of the RAS (Proceedings of ISP RAS). 2025;37(1):133-144. (In Russ.) https://doi.org/10.15514/ISPRAS-2025-37(1)-8
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