Who
Vinay Patwardhan, Senior Manager, Customer Support

What
What’s New – Fast Monte Carlo, statistical simulation technique
- Transient noise analysis
Notes
Overview – FineSim SPICE, FineSim PRO
- FineSim SPICE: multi-cpu capability (not multi-core with hyper threading), very linear speedup
- FineSim PRO:Fast Spice like NanoSim, HSIM, UltraSim. Does partitioning
- Also multi-cpu
- PRO includes FineSim SPICE
- Both
- Standard netlist formats (Hspice – not accuracy options, but post, scale, etc)
- IR and EM analysis
- Verilog and VHDL co-simulation
- Scalable
- Add more CPUS to get faster speeds
- Million transistors with 16 or 32 cpus
- Even single CPU is about 3 to 10x faster than HSPICE
- CPU means core (finesim –np 2, for 2 cores)
- If LSF network then give the LSF commands to use 4 cores across 2 CPUs
- No portioning, there is a single matrix yet multiple cores or CPUs solve it
- ADC 1.1k devices, 1 cpu 12x faster, 4 cpu, 35x
- PLL 10K, 8x, 27x
- Charge pump 8K, 7x, 17x
- Large analog block, 1.7M, 15 cpus, 16 hours
FineSim PRO
- Efficient Power net simulation
- CPU, 150K M, 1M R, 3.2M C, 1 cpu 2 hrs, 4 cpu .84 hrs
- SRAM: 900K M, 1.2M R, 4.3M C, 2.23 hrs 1 cpu, 1.19 hrs w 4 cpus
Timeline – 2006 Multi CPU
- 2007 FS Pro Multi CPU
- 2008 Verilog A, ADE integration, Titan ADX integration
- 15 of 20 semiconductor companies use it
- TSMC qualified for 65nm and 40nm processes
New in 2010 – Fast Monte Carlo analysis
- Financial industry and mechanical used fast monte carlo
- What? Process variation parameters are increasing with smaller nodes
- How to accurately simulate process variations?
- Device size variation for a ring oscillator. Output waveform has a variation
- Traditional MC varies parameters (300 simulations). Std deviation versus #of iterations. How many iterations is enough?
- Beyond 1,000 simulations is not feasible.
- To achieve 95% confidence level (for a 1% error) in a normal data set:
- 1 sigma, 724 runs
- 2 sigma, 2006 runs
- 3 sigma 15K
- 4 sigma 315K
- 5 sigma, 19 million
- 6 sigma, 3B
- FMC dynamically samples
- Works towards a specified goal (mean, std. deviation, probability) with a given error tolerance
- Guarantees accuracy
- Supports finesim parallel technology
- Accepts industry standard parameter variation specification
- Other simulators cannot define a goal
- Find distribution:Y (Traditional), Y FineSim Fast MC
- Typical iterations: 100-1000, 50-100
- Convergence: slow, fast
- Find probability:no, yes
- User specificed tolerance: no, yes
- Global/local variation: yes, yes (in tsmc files)
- Example: clock path delay
- TMC: 25 runs, 8.629n mean delay, 22.78p std deviation, max error ?
- TMC: 300 runs, 8.615ns, 5.066p, ? (you still don’t know your maximum error)
- FMC: 25 runs, 8.615n, 4.524p, <2p max error
- FMC: 89 runs, 8.614n, 5.044p, <1ps max error
- Example: Band gap circuit, current measurement
- 1,000 iterations with traditional mc
- Set a target, then fmc will reach your goal in fewer iterations
- Example: Amplifier gain
- Number of sims: trad 13,055, fmc 1,039
- Math applied based on public domain papers
- Example: Bit cell of SRAM
- Does the bit cell flip?
- 6 sigma analysis of a memory bit cell failure (take millions in traditional)
- 1 cpu, 25 min
- 4 cpu, 5 min
- 9 cpu, 2 min
- Estimated probability = 2.499e-12
- 17,382 runs required
- Pricing per cpu?
- Summary
- Use finesim fmc for sign-off simulation
- 10x fewer iterations
- Parallel technology to get done quicker
- Transient Noise Analysis
- Device noise limits analog/rf circuits
- Noise would slow down circuit simulation
- Signal to Noise Ratio and Bit Error Rate
- White, flicker, thermal, shot simulated
- Noise source added
- Spectre and hspice netlists
- Slows down simulation run times
- Example
- PLL: 4.57 hours (2 hours without noise analysis)
- Q: Is noise based on anything from the foundry? A:No, it’s based on your experience.
- I supply min and max noise frequency.
- Multi cpu makes the run times acceptable
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