AI-Driven Verification for Compute Express Link (CXL): Challenges, Innovations, and Future

This comprehensive article explores the evolution and challenges of Compute Express Link (CXL) verification methodologies in modern computing environments. The article examines the critical aspects of cache coherency testing, compliance validation, and debugging strategies while highlighting the transformative role of artificial intelligence in enhancing verification processes. The article demonstrates how advanced methodologies address the complexities of heterogeneous computing systems by analyzing various verification approaches, including AI-driven compliance automation, predictive debugging, and adaptive testbenches. The article encompasses memory device verification performance, system-level integration, and future directions in CXL verification, providing insights into emerging technologies and methodologies for ensuring robust system validation.

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Publication Details

Journal
International Journal of Scientific Research in Computer Science Engineering and Information Technology
Published
2025-03-27
DOI
https://doi.org/10.32628/cseit25112728
Citations
2
Primary Topic
Software System Performance and Reliability
Type
article
Field-Weighted Citation Impact
2.97
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article

AI-Driven Verification for Compute Express Link (CXL): Challenges, Innovations, and Future

Deepak Kumar Lnu
2 citations
International Journal of Scientific Research in Computer Science Engineering and Information Technology
Software System Performance and Reliability
2.97
article

AI-Driven Verification for Compute Express Link (CXL): Challenges, Innovations, and Future

Deepak Kumar Lnu
article en
2 citations

Abstract

This comprehensive article explores the evolution and challenges of Compute Express Link (CXL) verification methodologies in modern computing environments. The article examines the critical aspects of cache coherency testing, compliance validation, and debugging strategies while highlighting the transformative role of artificial intelligence in enhancing verification processes. The article demonstrates how advanced methodologies address the complexities of heterogeneous computing systems by analyzing various verification approaches, including AI-driven compliance automation, predictive debugging, and adaptive testbenches. The article encompasses memory device verification performance, system-level integration, and future directions in CXL verification, providing insights into emerging technologies and methodologies for ensuring robust system validation.

International Journal of Scientific Research in Computer Science Engineering and Information TechnologyVol. 11(2)
National Society of Professional Engineers (US)
Openalex Percentile: Top 10%
Software System Performance and Reliability
2.97
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