In this paper we study the importance of accurate model-based simulation on characterization of the integrated circuit performance. We analyze device sensitivity to process variability and its impact on circuit timing. We show that only a small fraction of devices whose characteristics are significantly affected by process variability actually have correspondingly significant effect on the overall circuit performance. We suggest several ways to use this observation to improve robustness of circuits. We see that a significant fraction of devices is affected by the layout context and should be considered sensitive. However, and it is especially true in large designs, only a small fraction of these devices is critical for the circuit performance. Obviously, to make the design more robust we have to avoid devices which are both sensitive and critical
Early lithographic hotspot detection has become increasingly important in achieving lithography-friendly designs and
manufacturability closure. Fast physical verification tools employing pattern matching or machine learning techniques
have emerged as great options for detecting hotspots in the early design stages. In this work, we propose a
characterization methodology that provides measurable quantification of a given hotspot detection tool's capability to
capture a previously seen or unseen hotspot pattern. Using this methodology, we conduct a side-by-side comparison of
two hotspot detection methods-one using pattern matching and the other based on machine learning. The experimental
results reveal that machine learning classifiers are capable of predicting unseen samples but may mispredict some of its
training samples. On the other hand, pattern matching-based tools exhibit poorer predictive capability but guarantee full
and fast detection on all their training samples. Based on these observations, we propose a hybrid detection solution that
utilizes both pattern matching and machine learning techniques. Experimental results show that the hybrid solution
combines the strengths of both algorithms and delivers improved detection accuracy while sacrificing little runtime
efficiency.
A half-node process has been routinely used to deliver incremental improvements in process control and hardware
availability in order to continue Moore's Law. Traditionally, due to the imaging requirements, parameters such as
numerical aperture and partial coherence were not set to their maximum resolution settings, thus leaving room in
hardware and RET recipes to accommodate incremental imaging requirements. However, as hardware availability and
computational lithography methods are stressed to the maximum of their capabilities to deliver the next technology
nodes, it is worth asking the question if such optical shrinks continue to be viable moving forward. Already 28nm
layouts scaled down from the original 32nm layouts are starting to show signs of configuration limitations dictated by
the available imaging hardware.
In this paper we show that two-dimensional features determine the feasibility of migrating successfully to the next halfnode
even when one-dimensional metrics suggest that such migration should be possible. While it has been proposed
that methodologies that are based on fabrics can guarantee composability and are intrinsically easier to migrate to
smaller nodes, such approaches are mostly valid for processes in which the frequency distribution of the object to be
imaged remains compatible with the hardware and RET of choice. This paper suggests that the distribution and extent
of the layout fabric discontinuities present one of the major hurdles to composability. In other words, it is not only
necessary to determine the best pitch and width of the underlying fabric it becomes crucial to determine the distribution
of the discontinuities present in the layout to build discrete devices.
Given that the feasibility of a half-node process is determined mostly by its ability to achieve denser patterns without
non-trivial layout modifications, in this paper we show that it is important to start looking at the explicit layout
configuration aspects that determine layout printability. We have selected a pair of prototypical layout configurations
common across all technology nodes of interest and have determined their intrinsic failure conditions for a given
process.
The results indicate that for a well padded 32nm process it may still be possible to perform an optical 28nm shrink with
only a minimum of manual intervention, assuming that certain layout configurations are removed or carefully
monitored during production. However, the nature of the analysis suggest that moving forward to 22nm and in the
absence of higher-resolution hardware (i.e. EUV) optical shrinks that require little or no layout modifications to the
desired patterns to be printed may no longer be possible.
Advances in lithography patterning have been the primary driving force in microelectronics manufacturing processes.
With the increasing gap between the wavelength of the optical source and feature sizes, the accompanying strong
diffraction effects have a significant impact on the pattern fidelity of on-silicon layout shapes. Layout patterns become
highly sensitive to those context shapes lying within the optical radius of influence. Under such optical proximity effects,
manufacturability hot spots such as necking and bridging may occur. Studies have shown that manufacturability hot
spots are pattern dependent in nature and should be considered at the design stage [1]. It is desirable to detect these hot
spots as early as possible in the design flow to minimize the costs for correction.
In this work, we propose a hot spot prediction method based on a support vector machine technique. Given the location
of a hot spot candidate and its context patterns, the proposed method is capable of efficiently predicting whether a
candidate would become a hot spot. It takes just seconds to classify thousands of samples. Due to its computational
efficiency, it is possible to use this method in physical design tools to rapidly assess the quality of printed patterns. We
demonstrate one such application in which we evaluate the layout quality in the boundary region of standard cells. In the
conventional standard cell layout optimization process, lithography simulation is the main layout verification method.
Since it is a very time-consuming process, the iterative optimization approach between simulation and layout correction
[2] takes a long time and only a limited number of context patterns can be explored. We show that with the proposed hot
spot prediction method, for each standard cell, a much greater context pattern space can be explored, and the context
sensitivity of a hot spot candidate located near a cell boundary can be estimated.
A methodology for predicting on and off-state transistor performance is described in this paper. In general,
this flow consists of systematic Edge-Contour-Extraction (ECE) from devices under the manufacturing,
followed by device simulation. Gate parameter extraction calculates an equivalent gate length and width
(Leq, Weq) for non-rectangular gates. The methodology requires a model describing MOSFET behavior of
current versus width for various gate lengths and voltages. Non-rectangular gates are described by a
weighted sum of the currents from a discrete representation (i.e. Total gate current is determined by a
weighted sum since the current distribution is not homogeneous along the channel). Thus, for a given L, W
and V, the current should be discoverable from the calibrated model. This approach is more general than
previous work as both Leq and Weq are determined for a given voltage which permits the model to predict on
and off-current with a single spice netlist as opposed to previous work which only considered adjustments
to the channel length.
In this work, two transistor series at two different drawn pitch conditions (dense and isolated) were
manufactured, followed by state-of-the-art ECE. The contours obtained directly by SEM measurements
were used to perform an electrical device simulation for each individual transistor in the series.
This paper demonstrates the possibility to analyze the transistor's electrical performance at nominal and
off-process conditions. The presented simulation flow provides the advantage of early-in-time prediction of
the transistor performances, measuring large volume of devices in a fast and accurate fashion.
A circuit-topology-driven approach to Optical Proximity Correction (OPC) is presented. By tailoring device
critical dimension (CD) statistical distribution to the device function in the circuit, and ensuring that the CD
distribution stays within the correct (possibly variable) limits during process maturation and other process
changes, it can be an effective tool for optimizing circuit's performance/yield tradeoff in high-volume manufacturing.
Calibre's proprietary Programmable Electrical Rule Checks (PERC) module is used to recognize the
topology. Alternatively, an external static timing tool can be used to identify critical devices.
As CMOS feature size scales down to 65nm and below, challenges for device and circuit manufacturability are
emerging. As commonly seen in real designs, devices with distorted gate shapes and rough line-edges are manufactured
despite the applications of aggressive resolution enhancement techniques (RET). It has been shown that such irregular
gates could introduce significant extra leakage current. Existing tools and device models cannot handle non-rectangular
geometries. Therefore, it is critical that a modeling flow capable of handling such irregular devices is developed and
smoothly integrated into the post-lithography delay and leakage circuit analysis process. Previously proposed methods
either model an irregular transistor as two different rectangular devices, one for on and the other for off state analyses; or
they are difficult to be implemented. In this paper, we propose a new modeling approach that serves as a fast and simple
solution to this problem and overcomes these drawbacks. We found that by adjusting both gate length and width of the
equivalent device, a single equivalent rectangular device can be determined. Through TCAD and SPICE simulation
experiments, we demonstrate that our model can accurately capture both on and off currents of the modeled nonrectangular
gate device. The average error of our modeling approach is 1.6% for Ion and 7.5% for Ioff.
In a previous work we have shown a yield optimization metric and a technique that considers the effects of several
types of yield enhancement methods for a given layout. Those findings suggested that it is important to consider two
types of yield tradeoffs, local tradeoffs where addressing one yield loss mechanism degrades others in the immediate
vicinity of the correction (local optimization window), and global tradeoffs where the net effect of the correction can be
fully accounted only when considering neighboring optimization windows. Such conclusion was derived from the fact
that the locally optimized layouts did not completely realize the theoretically optimal yield, which was obtained from
the assumption that global tradeoffs could be fully resolved. This work focuses in the contribution that such global
tradeoffs have on the final yield score when accounted properly during the optimization.
While the previous work focused only in selecting the corrections that locally improved the yield score1, this work
evaluates the global interactions before and after a change, and the correction is only accepted if it improves the global
score. While the global optimization requires a more expensive computational process, the intention of this work is to
determine how close the optimal layout can be from its theoretical limit. Since the optimization is performed and
evaluated under four different types of processes in which the failure mechanisms vary in relative importance, it is
possible to derive conclusions as to the need of considering global effects when trading off runtime requirements with
quality of the correction.
We demonstrate a consolidated metric that can quantitatively express design quality with respect to multiple yield loss
mechanisms. Using this metric and the design analysis and optimization framework we have developed, we study the
effectiveness of different layout enhancements and the effect of combining multiple enhancements in a single layout.
Previous works attempted to select a single combination of design enhancements that presents the optimal trade-off
between different yield loss mechanisms and optimizes the total yield. We show that the optimal solution depends on
the layout features on a small scale, thus the best yield can be achieved by selecting different combinations of
enhancements in different locations. We introduce a general form of the cost function and compare different layout
configurations, taking into account lithography process variations, random defect distributions, and recommended
design rules. Since all layout configurations represent the same electrical devices, it is possible to dynamically
determine the most robust layout implementation according to the cost function that incorporates the relative
importance of each yield loss contributor. We compare the globally optimized layout, where the sequence of yield
enhancements is selected based on the overall design yield, with locally optimized layouts, where the enhancements are
fine-tuned for each location.
We show that when comparing different layout enhancements it is important to consider two types of yield tradeoffs,
local tradeoffs where the same layout feature impacts several yield loss mechanisms, and global tradeoffs where the net
effect of a particular type of layout enhancement depends on its location. By selectively applying yield enhancements to
the areas of the layout where they are needed we can considerably improve the overall design quality.
One of the challenges in establishing quantitative manufacturability metrics has been establishing a single design
quality metric able to describe how a given region in the layout would perform under a specific manufacturing process.
Historically, critical area analysis has been sufficient to evaluate the possible yield of a design, but as the relative
importance of systematic mechanisms increases, this purely statistical approach needs to be enhanced by incorporating
additional process information. In this paper we describe a consolidated metric and the system that can analyze multiple
process conditions and different configurations to arrive to an optimal solution. This solution is based on a cost function
which depends on the characteristics of the manufacturing process. A general form of the cost function and the
parameters defining individual process impacts are discussed and, to demonstrate the system, different layout
configurations are analyzed taking into account lithography process variations, random defect distributions, and
recommended design rules. Since all layout configurations represent the same electrical devices, it is possible to
dynamically determine the most robust layout implementation according to the cost function that incorporates the
current relative importance of each yield loss contributor.
We present a new methodology for a balanced yield-optimization and a new DFM framework which implements it. Our approach allows designers to dynamically balance multiple factors contributing to yield loss and select optimal combination of DFM enhancements based on the current information about the IC layout, the manufacturing process, and known causes of failures. We bring together the information gained from layout analysis, layout-aware circuit analysis, resolution enhancement and optical proximity correction tools, parasitics extraction, timing estimates, and other tools, to suggest the DFM solution which is optimized within the existing constraints on design time and available data. The framework allows us to integrate all available sources of yield information, characterize and compare proposed DFM solutions, quickly adjust them when new data or new analysis tools become available, fine-tune DFM optimization for a particular design and process and provide the IC designer with a customized solution which characterizes the manufacturability of the design, identifies and classifies areas with the most opportunities for improvement, and suggests DFM improvements. The proposed methodology replaces the ad-hoc approach to DFM which targets one yield loss cause at the expense of other factors with a comprehensive analysis of competing DFM techniques and trade-offs between them.
We present a theory for the exciton magnetoluminescence in GaAs/AlAs superlattices. We have found the energies of the exciton states, taking into account an additional exchange splitting, which has been found experimentally. This splitting is attributed to the symmetry reduction from D2d to C2v, and it should lead to the polarized luminescence under the appropriately polarized excitation. Instead, a non-polarized luminescence was observed. At present, there are two alternative models explaining this phenomena. We have calculated the effect of the magnetic field on the exciton levels splitting in GaAs/AlAs superlattices and demonstrated that the two models give very different results for the hole g-factor. We show that measurements of the luminescence polarization allow us to choose between the alternative models of this splitting. The exciton luminescence, while completely non-polarized at zero magnetic field, becomes partially polarized at some specific values of the magnetic field. At these points, a level crossing occurs and one of the splittings in the exciton multiplet becomes zero. We show that these values of the magnetic field are very different in the two models of the additional exchange splitting.
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