Timing Analysis with Waveform Propagation

Report
Moon-Su Kim, Sunik Heo, DalHee Lee, DaeJoon Hyun,
Byung Su Kim, Bonghyun Lee, Chul Rim,
Hyosig Won, Keesup Kim
Samsung Electronics Co., Ltd.
System LSI Division
• Dr. Cho Moon
• Dr. Peter Kim
• PrimeTime Group(Amrita, JW Jang)
• SiliconSmart Group(Moninder, JH Song)
1
• Introduction
• Background
• Library Characterization Waveform
• Waveform Propagation Using Library Noise Model
• Experimental Results
• Runtime Impact
• Conclusion
2
• Impact of Scaling
• Wire resistance is linearly increased according to process nodes
- Long tail due to wire resistance
• No significant change in wire capacitance
- Device pin cap has relatively larger impact on delay
- Accurate analysis of Miller effect between input and output pin is more important
<Wire Cap Trend>
<Wire Resistance Trend>
3
• Conventional timing analysis with non-linear delay model (NLDM)
• NLDM cannot consider Miller effect and long tail effect
• Timing analysis results can be more optimistic than SPICE results
• Composite current source (CCS) model results are similar to NLDM results
Drive
Strength
Strong miller
effect
Long tail effect
4
• Long tail effect
• Slew degradation by wire resistance  long tail
• Same input transition(30% ~ 70%)  different propagation delay : long tail
effect
waveform atWaveform
[email protected](real)
Waveform @Y(driver model)
output
Waveform @ next A(real)
Waveform @ next A(driver model)
waveform at end
of wire
Delay difference
due to tail of
waveform
Input
< Slew Degradation due to Wire >
output
< Long Tail Effect>
5
• Miller effect
• Impact on current stage delay
-
Large receivers that are lightly loaded can inject a bump back to the interconnect through the
Miller cap (similar to crosstalk)
Receiver acts as an aggressor driver even though there is no external crosstalk source.
• Impact on output waveform
-
Waveform is too distorted to be modeled by any pre-driver accurately
Distortion is instance specific and cannot be modeled by characterization
Representing this complex waveform with delay and slew is not accurate
6
• Goal is to drive library cells with waveforms that approximate real waveforms
• Need to consider both fast input slew with no RC network effect and slow input
slew with significant RC network effect
• Can control waveform shape by varying weights of linear ramp vs. exponential
component
• V_pre-driver = V_linear * ratio + V_exponential *(1-ratio)
• Can consider slew degradation at wire by using the lower ratio (more exponential
component)
• Pre-driver ratio (PDR) of 0.3 means 30% linear and 70% exponential
<Pre-driver model>
7
• Library noise model is required
• Library was characterized using a pre-driver waveform generated from a
mixture of linear ramp and exponential waveform
• Waveform propagation method
• Enable propagation of waveforms for both clock and data networks
• CCS-Noise  gate level simulation  accurate waveform propagation &
accuracy improvement on the delay and slew
Timing Model
Receiver Model
C1,C2
C1,C2 C1,C2 C1,C2
C1,C2
C1,C2 C1,C2 C1,C2
C1,C2
C1,C2 C1,C2 C1,C2
C1,C2
C1,C2 C1,C2 C1,C2
C1,C2
C1,C2
C1,C2
C1,C2
Driver Model
+
Noise Model
Miller Cap
+
-
+
-
Vi
=
Accurate Waveform
Propagation
+
Improved Path Delay
& Slew Accuracy
• How well STA consider waveform distortion
SPICE Waveform Results
Static Timing Analysis
Waveform Results
9
• Samsung structural test cases
• 415 test cases with 14nm technology
• Inverter / Buffer chains with various fanouts, parasitic loading, and driving
strengths
• Static timing analysis results using library noise model
• Waveform propagation analysis is enabled for graph-based analysis (GBA) and
path-based analysis (PBA)
• Path delay comparison with SPICE
NLDM
waveform propagation
PDR 0.5
PDR 0.3
PDR 0.5 PDR 0.3
GBA PBA
GBA
PBA
average
-6.0% -1.8% -4.8% -2.2%
-2.1% -1.6%
stdev
7.5%
6.4% 4.5% 1.5%
4.3% 1.5%
Accuracy significantly improved
with waveform propagation
10
• Comparison was made between two models:
• Old but very fast model (NLDM)
• New and most accurate model (waveform propagation)
• On a real 60 M instance design, waveform propagation was 14% slower
than NLDM
• Waveform propagation was enabled for both clock and data networks
• Runtime increase is tolerable for improved accuracy
NLDM
Waveform
Propagation
(min)
(min)
read_db
update_timing
104.9
157.3
113.9
175.0
PBA (max 10000 paths)
68.0
89.0
Total TAT
330.2
377.9
Ratio
1.00
1.14
11
• Studied waveform distortion due to long tail and miller effect
• Libraries were characterized using SiliconSmart
• Timing analysis was performed using PrimeTime
• SPICE results were obtained using HSPICE
• For accurate static timing analysis
• Pre-driver waveform with ratio 0.3 (30% linear ramp and 70% exponential)
provided the best accuracy for a slow corner library
• Accuracy significantly improved with waveform propagation
• Runtime degradation by waveform propagation is acceptable(14%)
12

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