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BEGIN:VEVENT
DTSTAMP:20240626T180034Z
LOCATION:Level 2 Exhibit Hall
DTSTART;TZID=America/Los_Angeles:20240624T170000
DTEND;TZID=America/Los_Angeles:20240624T180000
UID:dac_DAC 2024_sess232_ETPOST027@linklings.com
SUMMARY:AI-Assisted Design Optimization for Extensive Design Spaces: Handl
 ing 260,000+ Combinations
DESCRIPTION:Engineering Track Poster\n\nAustin Rhodes (Micron) and Mohamed
  Atoua (Siemens)\n\nThis presentation discusses how an AI-assisted design 
 optimization methodology provides a verified optimal solution for two circ
 uits: metal-option switches and charge pumps. By exploring the entire desi
 gn space, up to 260,000 design combinations in this case, it results in a 
 faster design cycle, improved capacity, and reduced CPU time.\n\nMicron us
 es metal-layer switches in its circuits for adjustment to changes. These s
 witches need tuning multiple times during a product design cycle; they mig
 ht also require adjustment post-tapeout if the process varies, causing poo
 r circuit performance. On the other hand, charge pumps are widely used in 
 memory design for converting a supply voltage to a higher or lower value.\
 n\nThe traditional tuning methods of the above-mentioned circuits involve 
 an iterative manual process to explore as many of the design combinations 
 as possible. This process is time-consuming and may lead to sub-optimal so
 lutions.\n\nThis presentation covers the motivation behind the work, the m
 ethodology used, and the results obtained by the design team. We also disc
 uss the algorithm behind the AI-powered solution that helped achieve these
  results.\n\nTopic: Back-End Design, Embedded Systems, Front-End Design, I
 P
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