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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM35736
Volume:
8 |
6 |
Jun 2024
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
High-performance GPU cores are essential for handling complex computations and parallel processing tasks, significantly outperforming traditional CPUs. The architectural complexity and diverse operating conditions of GPUs necessitate rigorous design and verification processes, with Static Timing Analysis (STA) being crucial for ensuring performance and reliability standards. This project enhances STA for high-performance GPUs by developing automation scripts using Perl, Python, and Flask, streamlining the process, reducing manual effort, and minimizing errors. Techniques such as VT swapping, buffer insertion, clock pushing, and advanced crosstalk mitigation are employed, demonstrating significant improvements in timing performance. The findings provide valuable insights for engineers and designers, contributing to the advancement of STA practices in the semiconductor industry. .
KEYWORDS
Publication Date
11/5/2024
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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