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VarMan: statistical variation and yield analysis for analog, library and memory

Know how your circuit behaves across process variation before silicon tells you, with Monte Carlo-accurate results up to 30X faster.

Talk to our Technical Experts Documentation

What VarMan does

A design can pass at typical corners and still miss its yield in real silicon. Find that after tapeout and you're paying for a re-spin. VarMan runs variation and yield analysis on analog, library and memory designs, so the miss shows up while you can still change the design. Brute-force Monte Carlo can take millions or billions of runs to answer that. A memory bit-cell may need checking to 7 sigma and beyond. VarMan gets there up to 30X faster, because machine learning and statistical sampling pick the cases worth simulating.

Capabilities

Seven analyses, validated on FinFET and FDSOI technology at advanced nodes. Your edition decides which ones you get: VarMan Analog, VarMan Library or VarMan Memory, with the XMA option on Memory.

  • Fast Monte Carlo

    What a full classical Monte Carlo run would tell you, at up to 30X the speed. You set the accuracy target.

    On a 28 nm bulk CMOS VCO, 587 VarMan runs stood in for the 50,000 Monte Carlo runs requested.

  • High-sigma analyses

    Performance limits: name the sigma you need and get the performance limits that hold at that yield. It takes few simulations, even when the design has more than one failure zone.

    Yield estimation: set a performance limit and get the yield out to 4–6 sigma and beyond from a small run count. You also see the process conditions behind each parametric fail.

    High Sigma Spread: one operation maps a cell's yield from low sigma to high. Your power, performance and area trade-offs rest on the full distribution. It stays accurate on the non-linear, non-Gaussian distributions advanced nodes produce.

  • Exploration and corners

    Variability eXplorer: you set the simulation budget. It finds where the design turns marginal, from 3 sigma up to high sigma. Then it names the corners and parameters driving it.

    True corner extraction: out of every possible PVT combination, it finds the few statistical corners that decide whether you reach a given yield. You simulate those and skip the rest.

  • Sensitivity

    Local variability analysis: shows which transistors local variation hits hardest, from a small number of runs. It copes with a very large parameter count. Those transistors are your hotspots.

  • Integration

    Keep your simulator. VarMan works with any golden SPICE simulator and design environment, and with transistor-level simulators whether they're third-party or proprietary. Results and waveforms open in the golden viewers you already use. The GUI follows a load-and-analyze model, and a simulation manager spreads jobs across LSF, SGE, OGE and Slurm clusters.

    Utilities: VarMan Bench sweeps temperatures, sub-circuits and parameter values in one batch; DK Qualifier covers design kit support; the Calculator converts a sigma level into equivalent Monte Carlo runs, with its confidence interval.

Works with

Takes in

Your design, its model set and a golden SPICE simulator, whether that's a third-party tool or Silvaco's own SmartSpice

Hands off to

Yield figures, the failing samples behind them, and waveforms.

  • VarMan XMA option, for yield across an entire memory
  • Golden viewers, where you open the results and waveforms

Applications

  • Analog designStatistical analysis of analog cells, fast enough to fit inside your design schedule.
  • RF designThe same fast Monte Carlo for AMS and RF ICs.
  • Standard cell and IO characterization3-sigma process corners and statistical verification of a full standard-cell library.
  • Memory and bit-cell yieldBit-cell yield out past 7 sigma, and whole-memory yield through the XMA option.

Proof and resources

  • Customer talk · SURGE 2022

    Silicon Creations: a 3 nm to 350 nm design flow on Silvaco tools

    Chung-Chun Chen, Director of Analog Design, on porting the IP supplier's designs across 12 foundries. Simulation runs on SmartSpice, Silos and Variation Manager.

  • Product brief · PDF

    VarMan variation-aware design solution

    All seven analyses and the three editions. Worked examples run from a 28 nm VCO to FinFET and 28 nm bit cells at 5.2 and 5.4 sigma.

  • Product brief · PDF

    VarMan for Libraries

    Statistical functional verification for standard-cell libraries, shown on a 28 nm FDSOI flip-flop and a 40-cell digital library.

  • Product brief · PDF

    VarMan XMA option: full-chip memory yield analyzer

    How XMA runs Monte Carlo across an entire memory instead of a slice, with an 8K × 80-bit SRAM example.

  • White paper

    VarMan fast Monte Carlo and high-sigma analyses for FDSOI bit cell design

  • White paper

    Variability-aware design: the VarMan solution

  • White paper

    VarMan for digital libraries

  • Conference talk · SURGE 2022

    VarMan high-sigma performance in a redesigned GUI

    Vincent Annezo, VarMan corporate application engineer, on the new GUI and algorithm changes, shaped by years of customer feedback.

  • WebinarJune 2020

    Machine learning in the EDA-specific domain: 20 years in the making

    How machine learning was adapted to EDA's limits: scarce, noisy data, short projects and growing variation at advanced nodes. Silvaco tools serve as the examples.

  • WebinarSeptember 2018

    Memory statistical characterization solution with VarMan

    Why 6- and 7-sigma memory verification takes too many simulations done the traditional way, and the VarMan analyses that cut them.

  • WebinarFebruary 2018

    Standard cell statistical characterization with VarMan

    Finding 3-sigma corners and running 6-sigma verification on a standard-cell library without the usual simulation count.

  • WebinarNovember 2016

    Statistical analysis flow for analog design with VarMan

    Where regular Monte Carlo runs out for analog designers, and how VarMan speeds up analog cells and AMS and RF ICs.

  • WebinarMarch 2016

    Variation-aware design for advanced nodes and low-power technologies

    Why FinFET, FDSOI and lower Vdd/Vth processes made Monte Carlo routine, and VarMan's sampling techniques for analog, memory and standard cells.

All variation and yield analysis white papers

Evaluate and engage

Bring a cell, its model set and the sigma it has to reach. Then talk through its variation and yield analysis with an engineer who knows VarMan.

Talk to our Technical Experts Documentation Support and Downloads

Questions about VarMan

Variation-aware design means checking that a circuit meets its specification across the process variation real silicon brings, rather than at typical corners alone. FinFET, FDSOI and lower supply and threshold voltages made heavy Monte Carlo use routine. Brute force costs time and simulation licenses, and VarMan cuts both.

High-sigma analysis checks that a design still meets spec at very rare failure rates, 4 to 6 sigma and beyond. You need it wherever a cell repeats many times over: memory bit-cells can call for 7 sigma or more, which brute-force Monte Carlo would need billions of simulations to reach. VarMan estimates that yield from a limited run count.

VarMan combines machine learning with statistical algorithms and sampling strategies. Instead of spreading simulations evenly, it concentrates them on the samples close to failure. You get the result classical Monte Carlo would give, at the same accuracy and up to 30X the simulation performance.

VarMan isn't tied to one simulator or design environment. Bring your golden SPICE simulator, third-party or proprietary, or run it with Silvaco's SmartSpice, and your existing flow stays as it is. Waveforms and results go to your golden viewers, and large jobs can run on LSF, SGE, OGE or Slurm clusters.

True corner extraction identifies the process, voltage and temperature settings behind the statistical corners most likely to deliver a target yield. Only those corners get simulated, not every PVT combination. On a 90 nm embedded-flash design, 3-sigma corner verification dropped from 142,000 SPICE runs to 422.

VarMan analyzes individual cells and circuits with Monte Carlo, high-sigma, corner and sensitivity analyses. The XMA option, an add-on to VarMan Memory, analyzes the yield of the entire memory instead of extrapolating from a slice or critical path. Underneath, VarMan's fast Monte Carlo and high-sigma engines find the fails and estimate yield quickly.

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