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DTSTART:19700308T020000
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BEGIN:VEVENT
DTSTAMP:20260402T024533Z
LOCATION:2008\, Level 2
DTSTART;TZID=America/Los_Angeles:20250623T160000
DTEND;TZID=America/Los_Angeles:20250623T161500
UID:dac_DAC 2025_sess215_ENGPRES126@linklings.com
SUMMARY:SuperCoverage: AI-Guided Full Coverage of Thermal and Power Analys
 is for SoC Design
DESCRIPTION:Xia Zhu, Jianfang Zhu, Mark Gallina, and Julien Sebot (Intel C
 orporation)\n\nTransient temperature response approximately follows an exp
 onential function of power density. As transistors keep shrinking due to M
 oore's Law turbo workloads in client processors are experiencing increased
  localized power density – resulting in increased transient temperature ra
 mp rates and large workload dependent on die thermal gradients. Each workl
 oad exhibits unique thermal response characteristics, and the variety and 
 volume of workloads are vast and continuously growing. Accurate measuremen
 t of actual hot-spot temperatures is crucial for effective processor dynam
 ic power and thermal control, as well as ensuring thermal reliability. To 
 address this challenge, we propose SuperCoverage, a novel approach that si
 gnificantly enhances workload coverage for power and thermal analysis by a
  factor of 100x while drastically accelerating the generation of power and
  thermal maps by a factor of 1000x.\n\nTopics: AI, Systems and Software, C
 hiplet\n\nSession Chair: Frank Schirrmeister (Synopsys)\n\n
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