Self-adapting reconfigurable multiply-accumulator for real-time image processing in embedded systems

Andrea Fasolino; Paola Vitolo; Rosalba Liguori; Luigi Di Benedetto; Alfredo Rubino; Gian Domenico Licciardo

doi:10.1117/12.3016834

20 June 2024 Self-adapting reconfigurable multiply-accumulator for real-time image processing in embedded systems

Andrea Fasolino, Paola Vitolo, Rosalba Liguori, Luigi Di Benedetto, Alfredo Rubino, Gian Domenico Licciardo

Proceedings Volume 13000, Real-time Processing of Image, Depth, and Video Information 2024; 1300007 (2024) https://doi.org/10.1117/12.3016834
Event: SPIE Photonics Europe, 2024, Strasbourg, France

Abstract

Multiply-Accumulate (MAC) operation is widely used in various real-time image processing tasks, ranging from Convolutional Neural Networks to digital filtering, significantly impacting overall system performance. In this work the Self-Adapting Reconfigurable Multiply-Accumulate (SR-MAC) is proposed as a new instrument to find the optimal trade-off between operation throughput, power consumption and physical resources utilization in real-time image processing applications. Operations of the proposed system rely on the dynamic reconfiguration of the hardware resources on the basis of the current computational requirements. This is achieved by monitoring overflow and over-representation occurrences at each accumulation cycle, and properly considering the relevant portion of the accumulation result. A custom architecture of the proposed algorithm has been designed and implemented on an AMD Xilinx Artix-7 FPGA through a Verilog description and compared to the AMD Xilinx fixed-point macro (floating-point fused multiply-accumulate). The SR-MAC achieves reductions of 83% (82%), 79% (93%) and 87.2% (94%) in the number of LUTs, FFs, and the power dissipation, P_dynN, respectively. The SR-MAC has also been used to replace arithmetic units in typical real-time image processing applications. In these cases, its employment has allowed the reduction up to 6% and 14% of FFs and P_dynN, respectively, while increasing up to 14% the f_Max. These results highlight the significant performance enhancement achieved with respect to both single operators and entire systems, making SR-MAC an excellent design choice in real-time image processing applications.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Andrea Fasolino, Paola Vitolo, Rosalba Liguori, Luigi Di Benedetto, Alfredo Rubino, and Gian Domenico Licciardo "Self-adapting reconfigurable multiply-accumulator for real-time image processing in embedded systems", Proc. SPIE 13000, Real-time Processing of Image, Depth, and Video Information 2024, 1300007 (20 June 2024); https://doi.org/10.1117/12.3016834

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