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AgO Analog RF Circuit Optimization
 

AgO Analog RF Circuit Optimization

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Analog and RF Circuit Optimization

Analog and RF Circuit Optimization
Hillol Sarkar
Hillol.Sarkar@ago-inc.com

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  • Database is effectively useful to determine the priority validation

AgO Analog RF Circuit Optimization AgO Analog RF Circuit Optimization Presentation Transcript

  • circuit optimum 5th generation
  • Strategic Advantage ASP Analog Signal Processing 1. Cutting edge tools 2. Knowledge base 3. Systematic approach to mitigate failures 4. Cost 5. Strategic Planning
  • Optimization Strategy Constraints Test Bench Tune Circuit Stable DC Operation Circuit DCSpecification AgO Feasibility Schematic Saturation Integrated Work Flow Global Monte Carlo Optimum Simulation Optimized db W/L What-if analysis All Process Centering Corners Parasitic Layout Extraction
  • AnXplorer GUI F G C P Stop HELPVariables OptionsTechnology AnalysisCost Graph LogDB Queries Output F = Feasibility Study G = Global Optimization C = Centering P = Porting
  • Analog Design Structure System SoC (Single Chip 4G Tx Rx) Function ADC DAC PLL SerDes Circuit Current Sink Op Amp Current Mirror Level Shifter CMOS GaAsComponent BJT GaN
  • Optimization Strategy Feasibility Global Optimization Centering DatabaseDescription Description Description Description• DC Operation • Single Corner • All Corners • Conflict• Increase Margin • Meet performance • Rapid Size • Change Priority• Quick check • Monte Carlo • Ready for P&R • System Analysis• Best Design Space • Ready for Center AgO Optimization Strategy
  • Monte Carlo Statistical Control StrategyCircuit • Schematic • Spice Net List Feasibility Global CenteringSimulation • Test Bench • ConstraintsObjectives • Objectives AgO Algorithm • Min Max RangesProcess • Process Corners • Non-Statistical Six Sigma Database Optimized W/LStatistical Process • Process Corners • 6 Sigma based optimization Monte Carlo based optimization Refer User’s Manual 3.7.6
  • Monte Carlo Simulation In MC simulation we follow the time dependence of a model for which changes proceed in a stochastic manner. It depends on sequence of random numbers. The random numbers are generated during Monte Carlo simulation. Random Random Numbers 6 Sigma Random Random Stochastic resonance In biological systems, introducing stochastic noise has been found to help improve the signal strength of the internal feedback loops for balance and other vestibular communication.
  • Application Management Strategy Spice Net List Schematics dc operation RelativeTest Bench AgO Priority Implicit Database Simulation What-if analysis Objectives Circuit performances
  • Road Map Road Map Integration Fast • 2013 • 2012 Slow • 2011Importance for Market Monte Carlo Cadence Mentor Algorithm MSIM • Product Ready • Cadence • Mentor • MSIM 2007 to 2013
  • Power Amplifier
  • Jazz Avishai Cohen of Third World Love
  • Sensors for Food 50B devices connected
  • Illumina Genome Sequencing $1K
  • Hospital @ Home
  • Personal Medical Information Transmitter
  • London Wi-Fi Trash Can
  • Transportation
  • Life style
  • System on a Chip
  • Alcatel Lucent Broadband everywhere is speeding up life and business. It takes no time to touch people’s lives. Innovate at the speed of light. Ben Verwaayen CEO Alcatel Lucent Near Field Communication NFC 60 GHz – Mobile transaction will cross $1T by 2016
  • AgO High Street
  • Global Contacts USA: Jim.Smith@ago-inc.com Europe: David.Wood@edasip.com Japan: Yoshio Inoue y-inoue@revsonic.com Marketing: Hillol.Sarkar@ago-inc.com www.ago-inc.com Hillol.Sarkar@ago-inc.com