A Multi-Source AXI4-Stream Arbiter with Priority-Based Flow Control for Heterogeneous AI Systems

DOI

10.2991/978-94-6239-791-0_39How to use a DOI?

Keywords

AXI4-Stream; Multi-source Arbiter; FPGA; ASIC; FIFO; Flow Control

Abstract

While data movement latency is still a big problem for AI with heterogeneous systems. To overcome this, we are introducing a Multi-source AXI4-Stream interconnect with an input arbitration scheme Implement stage and asynchronous FIFO buffers for robust data flow by Between different processing elements. Implemented on an Intel MAX 10 FPGA and synthesized device with TSMC 100MHz 65nm technology node. the design exhibits high performance, deterministic communication. At a FPGA clock frequency of 50MHz the experimental results yield a peak Can achieve a throughput of 400 MB/s with just 4% of the logic resources. Compact silicon readiness with ASIC synthesis. footprint of 109, 124 μm² and a setup slack of 8,408ps at 100 MHz. This Real-time depends on resource-efficient architecture as a key enabler. By ensuring that applications, especially AI linkages within remote surgeries, run efficiently. For mission-critical continuous, high precision data transmission is required.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Gaurav Nanaware
AU  - Ashwini Kulkarni
AU  - Varada Inamdar
PY  - 2026
DA  - 2026/10/09
TI  - A Multi-Source AXI4-Stream Arbiter with Priority-Based Flow Control for Heterogeneous AI Systems
BT  - Proceedings of the International Conference on Artificial Intelligence and Machine Learning for Agro-Ecosystems (ICAIML-AE 2026)
PB  - Atlantis Press
SP  - 524
EP  - 534
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6239-791-0_39
DO  - 10.2991/978-94-6239-791-0_39
ID  - Nanaware2026
ER  -