arXiv:2511.12581v2 Announce Type: replace Abstract: Static IR drop analysis is a fundamental and critical task in the field of chip design. Nevertheless, this process can be quite time-consuming, potentially requiring several hours. Moreover, addressing IR drop violations frequently demands iterative analysis, thereby causing the computational burden. Therefore, fast and accurate IR drop prediction is vital for reducing the overall time invested in chip design. In this paper, we firstly propose a novel multimodal approach that efficiently processes SPICE files through large-scale netlist trans
The increasing complexity of chip designs and the demand for faster time-to-market are driving the need for more efficient analysis tools, making this development timely for the semiconductor industry.
This development could significantly accelerate the chip design process by reducing the time-consuming IR-drop analysis, which is a critical bottleneck in semiconductor manufacturing.
The proposed LMM-IR framework introduces a multimodal approach utilizing large-scale netlist processing, potentially reducing iterative analysis and overall chip design time.
- · Semiconductor companies
- · Chip design software providers
- · High-performance computing sector
- · Traditional static IR-drop analysis software
- · Companies reliant on older, slower design methodologies
Faster and more efficient chip design and verification processes will lead to quicker product cycles.
Reduced design costs and improved chip performance as a result of optimized power delivery networks.
Accelerated innovation in AI hardware and specialized compute, benefiting from a more streamlined design pipeline.
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