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DTSTAMP:20240626T180033Z
LOCATION:Level 2 Exhibit Hall
DTSTART;TZID=America/Los_Angeles:20240625T170000
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UID:dac_DAC 2024_sess233_ETPOST146@linklings.com
SUMMARY:Machine Learning Optimization Switch cells.
DESCRIPTION:Engineering Track Poster\n\nSungsu Byun (Samsung)\n\nPower gat
 ing design is essential to save the power. It is important not only to des
 ign PDN (power delivery Networks) but also to place switch cells in terms 
 of number and distributions.\nIt is necessary of switch cell ratio as Desi
 gn Methodology to get robust power integrity by considering Static IR, Dyn
 amic IR and Leakage from powerplan to eco.\nHowever, designer face difficu
 lty of Switch cells estimation as power from Switch cells in advance.\n So
 , in ECO stage, if it there is not enough Switch cell, hard to insert more
  additional Switch cells in the empty area and to create additional PDN fo
 r Switch cell.\nTo solve the issues, optimal switch cell methodology is ne
 cessary with Machine learning.\nBased on Linear Regression, optimal switch
  solution could be made by input parameters.\nWithout any tradeoff, design
  can be more robust. It leads to better Power integrity and TAT.\n\nTopic:
  Back-End Design, Embedded Systems, Front-End Design, IP
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