With process technologies advancing to 65nm, 45nm, and below, device timing uncertainty due to lithography and other
process variations has easily exceeded 50% and is still growing. In this paper, we present the development of a
variability methodology, its correlation with silicon and application to cell and full-chip design verification and
optimization. We describe both a methodology for variability analysis of standard cells and a full-chip screening
methodology to identify potential chip variability excursions. This methodology relies on model-based analysis and
integrates with our existing design-to-manufacturing flow. Based on silicon measurement data of one of our 65nm cell
libraries, this methodology has achieved significant improvement in accuracy of estimating timing variations compared to a traditional rule-based method.
KEYWORDS: Lithography, Chemical mechanical planarization, Design for manufacturing, Model-based design, System on a chip, Manufacturing, Metals, Databases, Design for manufacturability, Semiconductors
In this paper, we present the challenges of the realization of a large 45nm modern Media Processing SoC with multiple
design teams distributed across many countries and time zones. We also describe the complex design methodology
deployed to ensure the design is "closable" in the timing and manufacturability domain.
Silicon variability impacts both the physical integrity and the parametric performance of the design. Lithography and
CMP can cause enough context-dependent systematic variations, requiring exhaustive lithography and CMP physical
verification and optimization of the layout.
We present the physical and electrical DFM methodology at NXP. We will show how NXP has developed a
manufacturing-aware design flow based on early prevention, detection and fixing using a hierarchical approach for
model-based lithography checks and model-based CMP checks, from IP level to full-chip. We also present results of
variability-aware timing sign-off.
We have conducted a study of context-dependent variability for cells in a 45nm library, including both lithography and
stress effects, using the Cadence Litho Electrical Analyzer (LEA) software. Here, we present sample data and address a
number of questions that arise in such simulations. These questions include identification of stress effects causing
context dependence, impact of the number of contexts on the results, and combining lithography-induced variations due
to overlay error with context-dependent variations. Results of such simulations can be used to drive a number of
corrective and adaptive actions, among them layout modification, cell placement restrictions, or optimal design margin
determination.
To address the variability challenges inherent to 45 and 32nm as early as possible, a model-based variability analysis has
been implemented to predict lithography induced electrical variability in standard cell libraries, and this analysis was
used optimize the cell layout and decrease variability by up to 40%.
Leveraging silicon validation, a model-based variability analysis has been implemented to detect sensitivity to systematic
variations in standard cell libraries using a model-based solution, to reduce performance spread at the cell level and chip
level. First, a simulation methodology to predict changes in circuit characteristics due to systematic lithography and etch
effects is described and validated in silicon. This methodology relies on these two foundations: 1) A physical shape
model predicts contours from drawn layout; 2) An electrical device model, which captures narrow width effects,
accurately reproduces drive currents of transistors based on silicon contours. The electrical model, combined with
accurate lithographic contour simulation, is used to account for systematic variations due to optical proximity effects and
to update an existing circuit netlist to give accurate delay and leakage calculations.
After a thorough validation, the contour-based simulation is used at the cell level to analyze and reduce the sensitivity of
standard cells to their layout context. Using a random context generation, the contour-based simulation is applied to each
cell of the library across multiple contexts and litho process conditions, identifying systematic shape variations due to
proximity effects and process variations and determining their impact on cell delay.
This methodology is used in the flow of cell library design to identify cells with high sensitivity to proximity effects and
consequently, large variation in delay and leakage. The contour-based circuit netlist can also be used to perform accurate
contour-based cell characterization and provide more silicon-accurate timing in the chip-design flow. A cell-variability
index (CVI) can also be derived from the cell-level analysis to provide valuable information to chip-level design
optimization tools to reduce overall variability and performance spread of integrated circuits at 65nm and below.
The impact of lithography-induced systematic variations on the parametric behavior of cells and chips designed on a TI
65nm process has been studied using software tools for silicon contour prediction, and design analysis from contours.
Using model-based litho and etch simulation at different process conditions, contours were generated for the poly and
active layers of standard cells in multiple contexts. Next, the extracted transistor-level SPICE netlists (with annotated
changes in CD) were simulated for cell delay and leakage. The silicon contours predicted by the model-based litho tools
were validated by comparing CDs of the simulated contours with SEM images. A comparative analysis of standard cells
with relaxed design rules and restricted pitch design rules showed that restrictive design rules help reduce the variation
from instance to instance of a given cell by as much as 15%, but at the expense of an area penalty. A full-chip variability
analysis flow, including model-based lithography and etch simulation, captures the systematic variability effects on
timing-critical paths and cells and allows for comparison of the variability of different cells and paths in the context of a
real design.
With increasing chip sizes and shrinking device dimensions, on-chip semiconductor process variation can no longer be
ignored in the design and signoff static timing analysis of integrated circuits. An important parameter affecting CMOS
technologies is the gate length (Lgate) of a transistor. In modern technologies, significant spatial intra-chip variability of
transistor gate lengths, which is systematic as opposed to random, can lead to relatively large variations in circuit path
delays. Spatial variations in Lgate affect circuit timing properties, which can lead to timing errors and performance loss.
To maximize performance and process utilization in microprocessor designs, we have developed and validated a timing
analysis methodology based on accurate silicon contour prediction from drawn layout and contour-based extraction of
our designs. This allows for signoff timing without unnecessarily large margins, thereby reducing chip area and
maximizing performance while ensuring chip functionality, improved process utilization and yield. In this paper, we
describe the chip timing methodology, its validation and implementation in microprocessor design.
A methodology to predict the impact of systematic manufacturing variations on the parametric behavior of standard
cells in an integrated circuit is described. Such a methodology can be applied to the analysis of a full chip composed
of standard cell components, and reports layout context-dependent changes in chip timing and power. For
lithography and etch-induced variability, a study of a 65nm standard cell library has been done to examine the
influence of cell context when looking at cell delay and leakage at different focus and exposure conditions. Cell
context, or proximity effects from neighboring cells, can have a significant impact on cell performance across a
process window, especially through focus, which needs to be considered for silicon-aware circuit analysis. The
traditional lookup table approach used in static timing analysis or leakage power analysis needs to be augmented
with an instance-specific offset for each cell in a design. Contours need to be generated for each transistor in each
cell at different process points and the corresponding delay and leakage offsets should be calculated based on these
contours. Electrical characterization also enables the use of other context-specific process models, such as strain and
dopant fluctuations, without altering the final output. This allows subsequent tools to use the information for circuit
analysis. Such a methodology is thereby useful for process-aware static timing and power analysis.
Model-based hotspot detection and silicon-aware parametric analysis help designers optimize their chips for yield,
area and performance without the high cost of applying foundries' recommended design rules. This set of DFM/
recommended rules is primarily litho-driven, but cannot guarantee a manufacturable design without imposing overly
restrictive design requirements. This rule-based methodology of making design decisions based on idealized
polygons that no longer represent what is on silicon needs to be replaced. Using model-based simulation of the
lithography, OPC, RET and etch effects, followed by electrical evaluation of the resulting shapes, leads to a more
realistic and accurate analysis. This analysis can be used to evaluate intelligent design trade-offs and identify
potential failures due to systematic manufacturing defects during the design phase.
The successful DFM design methodology consists of three parts:
1. Achieve a more aggressive layout through limited usage of litho-related recommended design rules.
A 10% to 15% area reduction is achieved by using more aggressive design rules. DFM/recommended
design rules are used only if there is no impact on cell size.
2. Identify and fix hotspots using a model-based layout printability checker.
Model-based litho and etch simulation are done at the cell level to identify hotspots. Violations of
recommended rules may cause additional hotspots, which are then fixed. The resulting design is ready for
step 3.
3. Improve timing accuracy with a process-aware parametric analysis tool for transistors and interconnect.
Contours of diffusion, poly and metal layers are used for parametric analysis.
In this paper, we show the results of this physical and electrical DFM methodology at Qualcomm. We describe how
Qualcomm was able to develop more aggressive cell designs that yielded a 10% to 15% area reduction using this
methodology. Model-based shape simulation was employed during library development to validate architecture
choices and to optimize cell layout. At the physical verification stage, the shape simulator was run at full-chip level
to identify and fix residual hotspots on interconnect layers, on poly or metal 1 due to interaction between adjacent
cells, or on metal 1 due to interaction between routing (via and via cover) and cell geometry.
To determine an appropriate electrical DFM solution, Qualcomm developed an experiment to examine various
electrical effects. After reporting the silicon results of this experiment, which showed sizeable delay variations due
to lithography-related systematic effects, we also explain how contours of diffusion, poly and metal can be used for
silicon-aware parametric analysis of transistors and interconnect at the cell-, block- and chip-level.
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