Articles | Open Access | DOI: https://doi.org/10.37547/tajet/Volume07Issue03-22

Integrating Power-Saving Techniques into Design for Testability of Semiconductors for Power-Efficient Testing

Vijayaprabhuvel Rajavel , Semiconductor Design & Test Specialist, California, USA

Abstract

This article addresses the issue of improving energy efficiency in the testing of system-on-chip (SoC) semiconductor systems, including heterogeneous computing cores and AI accelerators. An analysis of SoC architecture and existing Design for Testability (DFT) methodologies is presented, considering energy-saving techniques such as clock gating, power gating, and dynamic voltage and frequency scaling (DVFS). A literature review highlights the insufficient development of a comprehensive approach to reducing power consumption specifically during testing procedures. Practical examples, including Qualcomm Snapdragon, Apple A-Series, and Tesla FSD, demonstrate that integrating low-power techniques into DFT can significantly reduce energy consumption (by an average of 20–35%) without compromising test coverage quality. The proposed analysis confirms the effectiveness of combining traditional scan chains, built-in self-test (BIST), and boundary scan with power management mechanisms, contributing to reduced thermal loads and increased reliability of modern SoCs in mass production. The findings presented in this article will be of interest to leading researchers and practicing engineers in the fields of microelectronics, materials science, and energy optimization, aiming to integrate advanced testing methodologies with innovative energy-saving solutions to develop reliable, high-performance, and environmentally sustainable semiconductor systems.

Keywords

System-on-chip, SoC, Design for Testability (DFT), energy efficiency, clock gating

References

Gupta M., Gupta S., As well P. Comprehensive Analysis of System on Chip: Architecture, Applications, and Future Trends. – 2024. [Electronic resource] Access mode:https://www.authorea.com/doi/full/10.22541/au.172977161.13847266 (date of request: 02/03/2025).

Leelakrishnan S., Chakrapani A. Power Optimization in Wireless Sensor Network Using VLSI Technique on FPGA Platform, Neural Processing Letters. – 2024. – Vol. 56 (2). – pp. 125.

Nielsen C. Navigating the Seas of Change, Canadian Journal of Medical Laboratory Science. – 2016. – Vol. 78 (4). – pp. 48-60.

Semiconductor Industry Association et al. ITRS: International technology roadmap for semiconductors . – 2015.- pp. 34-39.

Hennessy, J. L., Patterson, D. A. Computer Architecture: A Quantitative Approach, Morgan Kaufmann Publishers. – 2019. – pp. 7-25.

Jouppi N. P. et al. A domain-specific architecture for deep neural networks, Communications of the ACM. – 2018. – Vol. 61 (9). – pp. 50-59.

Sze V. et al. Efficient processing of deep neural networks: A tutorial and survey, Proceedings of the IEEE. – 2017. – Vol. 105 (12). – pp. 2295-2329.

Kim, N. S., et al. 3D Stacking and Heterogeneous Integration: Process and Design Challenges, Proceedings of the 55th Annual Design Automation Conference (DAC). – 2018. – pp. 15-35.

Marwedel P. Embedded system design: embedded systems foundations of cyber-physical systems, and the internet of things. – Springer Nature, 2021. – pp. 433.

Low Power Design for Testability . [Electronic resource] Access mode: https://www.design-reuse.com/articles/32262/low-power-design-for-testability.html (date of request: 11/03/2024).

Khursheed S., Al-Hashimi B. M. Test Strategies for Multivoltage Designs, Power-Aware Testing and Test Strategies for Low Power Devices. – 2010. – pp. 243-271.

Shetty S. K., Mohapatra E. Design and Testing of Low Power Cache Memory, 2024 8th International Conference on Computational System and Information Technology for Sustainable Solutions (CSITSS). – IEEE, 2024. – pp. 1-5.

Thota S. et al. Multi-Threshold CMOS Technology SAFF for High Speed and Low Power Applications, 2024 Second International Conference Computational and Characterization Techniques in Engineering & Sciences (IC3TES). – IEEE, 2024. – pp. 1-4.

Sariki A. et al. ASIC Design using Post Route ECO Methodologies for Timing Closure and Power Optimization, Int. J. Microsystems IoT. – 2023. – Vol. 1. – pp. 195-204.

Häffner S. et al. Introducing an interpretable deep learning approach to domain-specific dictionary creation: A use case for conflict prediction, Political Analysis. – 2023. – Vol. 31 (4). – pp. 481-499.

Power-Aware Test: Addressing Power Challenges In DFT And Test. [Electronic resource] Access mode: https://semiengineering.com/power-aware-test-addressing-power-challenges-in-dft-and-test/ (date of request: 06/03/2024).

Article Statistics

Copyright License

Download Citations

How to Cite

Vijayaprabhuvel Rajavel. (2025). Integrating Power-Saving Techniques into Design for Testability of Semiconductors for Power-Efficient Testing. The American Journal of Engineering and Technology, 7(03), 243–251. https://doi.org/10.37547/tajet/Volume07Issue03-22