As we enter the curvilinear mask and multi-beam writer era, a new fracture engine is needed. In this presentation we introduce an innovative fracture engine called SmartFracture. The new engine can handle the Bezier curves natively, which enables high accuracy and smaller output file size. We will explore the characteristics of Bezier curve data representation and full chip results with the new engine.
Curvilinear layout data has been used for better mask quality for ILT OPC results, but it has issues such as complexity, huge data volume and absence of established verification methods. In this presentation, fundamental and practical verification methods will be discussed for complicated curvilinear geometries. On top of that, real curve data (parametric curves) has been discussed to reduce the mask data volume. The MULTIGON record has been defined as the real curve expression. We will explain the characteristics of the new record and show the outlook about how the mask industry should deal with its complexity.
This conference presentation was prepared for Photomask Japan 2022: XXVIII Symposium on Photomask and Next-Generation Lithography Mask Technology, 2022.
Model Based Mask Process Correction (MB-MPC) has been deployed in the photomask manufacturing process for almost a decade. It has now become a must have process for leading edge masks that require high level manufacturing accuracy. Recently, aggressive OPC methods such as ILT have significantly increased the complexity of mask data. This impacts Mask Data Preparation’s (MDP) processing time due to large mask data volumes. By its nature, MB-MPC process is quite time-consuming since it needs to perform complex calculations repeatedly, and so it takes the largest part of the total MDP time. This puts high pressure on turn-around time (TAT) reduction without losing accuracy and necessitates the need to develop algorithms that can operate on tight TAT budgets. Pattern Matching (PM) approach could be used to mitigate high processing times of MB-MPC by leveraging inherent repetitiveness of real-world mask data. Since a pattern simulation result is influenced by all patterns located within the mask model radius, to consider one pattern as a repetition of another, the central pattern as well as the neighborhood must match. This method is called Neighborhood Pattern Matching (NPM). In this paper, we evaluate the effectiveness of NPM when applied to the MB-MPC software developed by Synopsys. First, we introduce the fundamental concepts of NPM. Then we validate the algorithm with test patterns to evaluate its behavior. Finally, we measure processing time with several types of device patterns and confirm how NPM can reduce MPC calculation time on real mask data.
Pattern matching seems to be promising technique to the mask industry. It can be used for many applications such as hot
spot detection of post-OPC data, search of AIMS reference location or CDSEM measurement point extraction. In particular,
fuzzy pattern matching is more needed for mask data processing because the mask layout has different derivatives generated
by OPC and there are many similar "OPC brothers" that come from the same layout. However, application of fuzzy pattern
matching to the mask layout is challenging due to the reasons related to the characteristics of photomask data.
In this paper we introduce a novel method of fuzzy pattern matching to cope with the issues that comes from the
characteristics of mask data. The rule specification is quite simple - we only need to specify a single tolerance value for each
edge displacement. We will show the experimental results using the actual mask layout and prove that the calculation speed
and quality of the proposed technique is satisfactory from the view point of realistic MDP processing.
Since the layout patterns on photomasks have been getting more and more complicated by OPC/RET processes, the
mask patterns need to go through the verification to check the mask manufacturability even though the layout is 'DRC
clean'. This verification process is called MRC (mask rule check). The fundamental functions required for MRC is
relatively simple, such as narrow gap detection between patterns. SII NanoTechnology has been developing an MRC
software product, SmartMRCTM, and it is widely used in mask shops as MRC standard software. Recently, in addition to
typical usages of MRC software, various realistic applications have been reported in order to solve problems related to mask
fabrication process. In this paper, we introduce three applications of MRC software for more efficient mask manufacturing.
GPGPU (General Purpose Graphic Processor Unit) has been attracting many engineers and scientists who develop their
own software for massive numerical computation. With hundreds of core-processors and tens of thousands of threads
operating concurrently, GPGPU programs can run significantly fast if their software architecture is well optimized. The
basic program model used in GPGPU is SIMD (Single Instruction Multiple Data stream), and one must adapt his
programming model to SIMD. However, conditional branching is fundamentally not allowed in SIMD and this limitation is
quite challenging to apply GPGPU to photomask related software such as MDP or MRC.
In this paper unique methods are proposed to utilize GPU for MRC operation. We explain novel algorithms of mask
layout verification by GPGPU.
The photomask cost is becoming one of the challenging issues in the semiconductor industry, as the cost of photomasks
has been rising year by year. ASET started Mask D2I (Mask Design, Drawing and Inspection Technology) project with the
sponsorship from the NEDO (New Energy and Industrial Technology Development Organization) in 2006 for the purpose
of the mask cost reduction. In earlier papers[1-5], we introduced the idea of photomask data prioritization method which is
referred to as Mask Data Rank (MDR). We have built our software system to convert Design Intent (DI) to MDR with
cooperation of STARC. Then we showed the results of experiments with mask data provided by semiconductor companies.
In this paper we show the additional report of mask inspection experiments using real photomasks. Then we show the
evaluation results about mask drawing time reduction using MDR flow. Finally we introduce detailed algorithm to extract
design intent from analog circuits.
The cost of photomasks has been rising year by year as the process node gets finer and the mask cost is becoming one of
the headaches in the semiconductor industry. For the purpose of the mask cost reduction, ASET started Mask D2I (Mask
Design, Drawing and Inspection Technology) project in 2006. In earlier papers[1-4], we introduced the idea of photomask
data prioritization method which is referred to as Mask Data Rank (MDR). We have built our software system to convert
Design Intent (DI) to MDR with cooperation of STARC. Then we showed the results of preliminary experiments with mask
data provided by STARC.
In this paper we explain the software mechanism of design intent extraction flow. Then we show the experimental results
with actual chip data in three semiconductor companies and address the related issues. Finally we introduce a new idea to extract design intent from analog circuits.
Mask D2I/ASET has been working to reduce TAT for mask writing and inspection. As a part of this program we have
developed a data flow process for mask manufacturing in which we refer to design intent information in order to reduce
TAT of mask manufacturing processes. We convert design level information "Design Intent (DI)" into priority
information of mask manufacturing data known as "Mask Data Rank (MDR)" so that we can identify and sort out the
importance of reticle patterns from the view point of the design side. As a result, we can reduce mask writing time and
mask inspection time significantly. Our objective is to build efficient data flow conversion system from DI to MDR.
Automatic DI creation flow from EDA tools, and an automatic MDR creation flow from the created DI have already
been established. We extracted design intents (Litho hotspot area, Shield net, Gate channel area, Timing critical net,
Dummy metal fill, Power ground net, etc.) from the database in EDA tools automatically, and converted them into MDR.
In an earlier paper, we had shown that by using this flow, we could achieve TAT reduction in mask writing and mask
inspection for a limited number of design data. In this presentation, we will show TAT reduction results for actual device
design data; we will then discuss related issues and their solutions.
Computational lithography appeared with people's expectation expanding to reduce total lithography cost and to
push the resolution limit for launching novel LSI fabrication processes and masks toward advanced LSI devices of
22 nm and beyond. Recently computational lithography grows up into an integration step to achieve the optimum
solution between an illumination source and a mask for creating the resist image on a wafer. This integration
scheme enables us not only to achieve ultimate single exposure but also to attain higher resolution beyond the
physical limitation by means of double patterning technique. The advanced computational lithography requires
massive data volume that urges us to construct further effective multi parallel methods. Photomask Japan
highlighted the computational lithography in a panel discussion titled "Mask Manufacturing with Massive or
Multi-parallel Method" and sub-titled "Massive or Multi-parallel" drives 22 nm (half pitch 32 nm) litho-mask
solution?" We reached a conclusion of "Enhancing computation power and more sophisticated computation
methods could solve the difficulties about further complicated computation".
KEYWORDS: Photomasks, Manufacturing, Inspection, Design for manufacturing, Analog electronics, Data conversion, Design for manufacturability, Semiconductors, Electronic design automation, Data processing
The problem of mask cost has been highlighted recently due to the complex manufacturing process as the semiconductor
node is getting smaller and smaller. It has been said that DFM methods can be useful for mask cost reduction. One of the
ASET/Mask D2I target is the mask data prioritization and its effective uses for mask manufacturing issues from the
viewpoints of mask DFM. The Mask D2I and STARC have been working together to build efficient data flow based on the
information transition from the design to the manufacturing level. By converting design level information called as "Design
Intent" to the priority information of mask manufacturing data called as "Mask Data Rank (MDR)", MDP or manufacturing
process based on the importance of reticle patterns is possible. Our main purpose is to build a novel data flow with the
priority information of mask patterns extracted from the design intent.
In this paper, we introduce a design intent extraction flow which has been newly developed and we show the effectiveness
of the fully automated MDR flow with actual chip data. In addition, we show how MDR flow can be applied to analog
circuits.
KEYWORDS: Photomasks, Inspection, Manufacturing, Design for manufacturing, Lithography, System on a chip, Optical proximity correction, Double patterning technology, Design for manufacturability, Semiconducting wafers
This is a report on a panel discussion organized in Photomask Japan 2008, where the challenges about "Mask
Complexities, Cost, and Cycle Time in 32-nm System LSI Generation" were addressed to have a look over the possible
solutions from the standpoints of chipmaker, commercial mask shop, DA tool vendor and equipments makers. The
wrap-up is as follows: Mask complexities justify the mask cost, while the acceptable increase rate of 32nm-mask cost
significantly differs between mask suppliers or users side. The efficiency progress by new tools or DFM has driven their
cycle-time reductions. Mask complexities and cost will be crucial issues prior to cycle time, and there seems to be linear
correlation between them. Controlling complexity and cycle time requires developing a mix of advanced technologies,
and especially for cost reduction, shot prices in writers and processing rates in inspection tools have been improved
remarkably by tool makers. In addition, activities of consortium in Japan (Mask D2I) are expected to enhance the total
optimization of mask design, writing and inspection. The cycle-time reduction potentially drives the lowering of mask
cost, and, on the other, the pattern complexities and tighter mask specifications get in the way to 32nm generation as well
as the nano-economics and market challenges. There are still many difficult problems in mask manufacturing now, and
we are sure to go ahead to overcome a 32nm hurdle with the advances of technologies and collaborations by not only
technologies but also finance.
KEYWORDS: Photomasks, Inspection, Manufacturing, Semiconducting wafers, Data conversion, Design for manufacturing, Semiconductors, Design for manufacturability, Reticles, Data processing
MaskD2I and STARC have been working together to build efficient data flow based on the information transition from the
design to the manufacturing level. By converting design level information called as "Design Intent" to the priority
information of mask manufacturing data called as "Mask Data Rank (MDR)", MDP or manufacturing process based on the
importance of reticle patterns is possible. Our main purpose is to build a novel data flow with the priority information of
mask patterns extracted from the design intent.
In EMCL2008, we introduced the idea of MDR and showed its potential effectiveness. Then we addressed an additional
idea called DIF(Design Intent File) instead of RAF (Rank Assign File) in PMJ2008. Since DIF contains all the coordinate
information necessary for mask data prioritization, it has been proved that mask engineers do not need to access the design
information any more. Recently the necessity of information linkage between mask processes and wafer processes has been
pointed out and we have started to build a new flow to share the mask data priority information.
In this presentation, we will address two new progresses of MaskD2I. One is a new rank assignment method to inspection
tools and the other is information feed forward to wafer process.
One of the ASET/MaskD2I target is the mask data prioritization and it effective uses for mask manufacturing issues. The
MaskD2I and STARC have been working together to build efficient data flow based on the information transition from the
design to the manufacturing level. By converting design level information called as "Design Intent" to the priority
information of mask manufacturing data called as "Mask Data Rank (MDR)", MDP or manufacturing process based on the
importance of reticle patterns is possible. Our main purpose is to build a novel data flow with the priority information of
mask patterns extracted from the design intent.
In this paper, we introduce the basic activities of the MaskD2I, and address the effectiveness of MDR information. Then
we explain how to apply it to mask writing, inspection, MDP and MRC. We will show the new experimental results by
extracted MDR from actual mask data provided by STARC.
KEYWORDS: System on a chip, Optical proximity correction, Data conversion, Inspection, Metals, Manufacturing, Electronics, Vestigial sideband modulation, Parallel processing, Software development
As the feature size of LSI becomes smaller, the increase of mask manufacturing cost is becoming critical. Association of
Super-Advanced Electronics Technologies (ASET) started a 4-year project aiming at the reduction of mask
manufacturing cost and TAT by the optimization of MDP, mask writing, and mask inspection in 2006 under the
sponsorship of New Energy and Industrial Technology Development Organization (NEDO). In the project, the
optimization is being pursued from the viewpoints of "common data format", "pattern prioritization", "repeating
patterns", and "parallel processing" in MDP, mask writing, and mask inspection. In the total optimization, "repeating
patterns" are applied to the mask writing using character projection (CP) and efficient review in mask inspection. In this
paper, we describe a new method to find repeating patterns from OPCed layout data after fracturing. We found that using
the new method efficient extraction of repeating patterns even from OPCed layout data is possible and shot count of
mask writing decreases greatly.
In order to go through the transition term from GDSII to OASIS successfully, the aid of the verification tools between
OASIS and GDSII is necessary. In general, we have two methods of OASIS file verification. One is a hierarchical method
that checks between GDSII and OASIS by each cell level. The other is a flat method that merges each pattern through its
hierarchy into a flat level and compares the flattened geometry one by one.
We did the experiments of comparison between two methods for OASIS to GDSII verification. The software tool called
'ogdiff' has been used for a hierarchical verification experiment. We used SmartMRC for the flat method experiment. In this
paper, we show the experimental results of comparison and we also address the pros and cons of each method. Then we
suggest which method is preferable for specific cases.
One of the ASET/MaskD2I target is the mask data prioritization and it effective uses for mask manufacturing issues. The
MaskD2I and STARC have been working together to build efficient data flow based on the information transition from the
design to the manufacturing level. By converting design level information called as "Design Intent" to the priority
information of mask manufacturing data called as "Mask Data Rank (MDR)", MDP or manufacturing process based on the
importance of reticle patterns is possible. Our main purpose is to build a novel data flow with the priority information of
mask patterns extracted from the design intent.
In this paper, we introduce the basic activities of the MaskD2I, and address the effectiveness of MDR information. Then
we explain how to apply it to mask writing, inspection, MDP and MRC. We will show the new experimental results by
extracted MDR from actual mask data provided by STARC.
As the feature size of LSI becomes smaller, the increase of mask manufacturing cost is becoming critical. Association of
Super-Advanced Electronics Technologies (ASET) started a 4-year project aiming at the reduction of mask
manufacturing cost and TAT by the optimization of MDP, mask writing, and mask inspection in 2006 under the
sponsorship of New Energy and Industrial Technology Development Organization (NEDO) [1]. In the project, the
optimization is being pursued from the viewpoints of "common data format", "pattern prioritization", "repeating
patterns", and "parallel processing" in MDP, mask writing, and mask inspection. In the total optimization, "repeating
patterns" are applied to the mask writing using character projection (CP) and efficient review in mask inspection. In this
paper, we describe a new method to find repeating patterns from OPCed layout data after fracturing. We found that using
the new method efficient extraction of repeating patterns even from OPCed layout data is possible and shot count of
mask writing decreases greatly.
Association of Super-Advanced Electronics Technologies (ASET) has started a project called "Mask Design, Drawing
and Inspection Technology (MaskD2I)" with the sponsorship from The New Energy and Industrial Technology Development Organization (NEDO) since 2006. SIINT has joined the MaskD2I project and we have been developing MRC software considering DFM information for more effective data verification. By converting design level information
called as "Design Intent" to the priority information of mask manufacturing data called as "Mask Data Rank (MDR)", the
MRC process based on the importance of reticle patterns is possible. Our main purpose is to build a novel data checking
flow with the priority information of mask patterns extracted from the design intent. In this paper, we address the effectiveness of MRC technologies which have been widely applied in many mask data
fields. Then we present the current status of the new MRC development, its experimental results so far and the future
outlook using further Design Aware Manufacturing (DAM) information.
KEYWORDS: Data conversion, Photomasks, Data analysis, Error analysis, Standards development, Electronic design automation, Nanotechnology, Data processing, Data compression
The OASIS (Open Artwork System Interchange Standard) format is a new standard format for describing LSI layout data
and it has begun to be used for photomask data. One of the greatest features of OASIS format is its conciseness of
expressing pattern data and it has been proven that the size of GDS2 files can be significantly reduced down by converting
them to OASIS format. It is widely believed that OASIS will replace the position of GDS2 format which is currently most
frequently used. In general, OASIS has two aspects for the mask industry. One is OASIS format as a new replacement of
GDS2. The other is OASIS.VSB, which is a unified format to be defined for the description of fractured EB data.
However, the mask industry has not shifted completely into OASIS and sometimes software operation for both OASIS
and GDS2 is required. In the environment of OASIS and GDS2 mixture, bi-directional data conversion between OASIS
and GDS2 is a key issue. When GDS2 data is converted to OASIS format, the file size always gets smaller and there is no
file size problem. But when OASIS data is converted to GDS2 format, the file size can be more than one hundred times
larger than the OASIS file, which sometimes causes hard disk space problems.
In order to cope with this problem, we have developed a file size estimation tool for OASIS to GDS2 conversion. The
name of the tool is "o2gest" and it is a member of SmartOASIS, which provides comprehensive practical functions to
enable easy transition of data processing flow from conventional GDS2 or EB formats to OASIS. The processing speed and
the calculation accuracy is a key issue for an estimation tool.
As patterns on photomasks are getting more complex due to RET technologies, mask rule check (MRC) has become an essential process before manufacturing photomasks. Design rule check (DRC) tools in the EDA field can be applied for MRC. However, photomask data has unique characteristics different from IC design, which causes many problems when handling photomask data in the same way as the design data.
In this paper, we introduce a novel MRC tool, SmartMRC, which has been developed by SII NanoTechnology in order to solve these problems and show the experimental results performed by DNP. We have achieved high performance of data processing by optimizing the software engine to make the best use of mask data's characteristics. The experimental results show that only a little difference has been seen in calculation time for reversed pattern data compared to non-reversed data. Furthermore, the MRC tool can deal with various types of photomask data and Jobdec in the same transparent way by reading them directly without any intermediate data conversion, which helps to reduce the overhead time. Lastly it has been proven that result OASIS files are several times smaller than GDS files.
OASIS format has begun to be accepted in the field of mask data processing gradually. Major EDA venders have announced their support of OASIS format and new versions of EDA tools which can handle with OASIS files have been shipped one by one. Still, there are great difficulties to convert all the data processing flow from old GDSII to new OASIS. One of the major issues is a problem of verification. Since all the tools have not been completely stable and reliable, there should be a method to verify whether the data is converted to OASIS without any problems. In addition to that, the integrity of the OASIS files itself have to be checked.
In general, OASIS has two aspects for the mask industry. One is a role as a new replacement of GDSII. The other is OASIS.VSB, which is a unified format defined for the description of fractured EB data. SII NanoTechnology has been developing a new software package called SmartOASIS. SmartOASIS provides lots of practical functions to enable easy transition of data processing flow from conventional GDSII or EB formats to OASIS.
KEYWORDS: Parallel processing, Photomasks, Image compression, Process control, Local area networks, Intellectual property, Data storage, Algorithm development, Control systems, Image processing
We have been developing intellectual properties (IP) protection software using OASIS format. In the Photomask Technology 2004 we presented that by taking advantage of repetition presentation of OASIS, it becomes possible to express arrayed patterns without any generation of new cells, which also brings less overhead and further compaction of the result file. As a result, we could rebuild the hierarchy without cell generation and reduce the output file size. In this paper, additionally we have applied a unique compression function CBLOCK defined in OASIS format. CBLOCK can compress any part of OASIS file. The experimental results show that there are no redundant cells generated and the file size has become approximately 20 times smaller than conventional methods.
KEYWORDS: Parallel processing, Data storage, Process control, Local area networks, Software development, Control systems, Nanotechnology, Photomask technology, Computing systems, Environmental sensing
In this paper we present new development of intellectual properties(IP) protection software using OASIS format. By taking advantage of repetition presentation of OASIS, it becomes possible to express arrayed patterns without any generation of new cells, which also brings less overhead and further compaction of the result file. As a result, we could rebuild the hierarchy without cell generation and reduce the output file size. The experimental results show that there are no redundant cells generated and the file size has become 5 to 8 times smaller than conventional methods.
The contact layer has been said to be the first application of NGL technologies such as EPL or LEEPL, in which stencil masks are used. Since the computation time depends on the number of edges of patterns, contact layer data which contains many rectangles takes very long time to process. Actually it has been reported that the complementary split of the contact layer patterns take longer time than any other layer like metal layer or poly line layer due to the numerous small rectangle patterns in the contact layer. This paper presents a new innovative algorithm, called gravity point method, to dispatch contact patterns very quickly onto complementary masks. The results show that the new gravity point method algorithm is effective for the huge size of contact layer data.
Mask data preparation (MDP) is a complicated process because many kinds of EB data files and jobdeck data files are used in mask manufacturers and EB data files continue to become bigger. Therefore we have developed unified mask data formats for Variable-Shaped-Beam (VSB) EB writers with efficient data compaction. The unified mask data formats are composed of a pattern data format for EB writers named "NEO" and a layout format named "MALY". We released NEO and MALY on April 2003. To evaluate NEO and MALY, we have made a prototype system of MDP such as a converter from design data to NEO/MALY and converters from NEO/MALY to each EB data. We have evaluated about functions and performance of the MDP flow using real design data in device manufacturers. As a result, some improvements in NEO and MALY were achieved and we have revised the specification of NEO and MALY as the final version. We have confirmed that NEO and MALY can be used for a set of unified mask data formats among VSB EB writers and can reduce complexity of mask data handling in mask manufacturers. They will be put to practical use in MDP flow.
KEYWORDS: Data conversion, Photomasks, Parallel processing, Reticles, Electronic design automation, Local area networks, Data modeling, Electron beams, Optical lithography, Manufacturing
EPLON is the name of a system that we have been developing as a data conversion system for EPL masks in order to meet the requirements of EPL stencil masks. In our paper we presented in PMJ2002, we proved that our system could convert the whole chip data. However we still had some problems to overcome, one of which is a problem of conversion time and another issue is a data volume problem. This paper presents the features of our multi process computation method and the data compaction with building a hierarchy from the flattened data.
We have developed the EPL mask data conversion system EPLON. It provides comprehensive capabilities necessary for the data conversion of EPL masks. This paper presents the features of each function and the evaluation result of data conversion with actual data on a full chip level. The result shows that the whole data conversion is possible within reasonable time for huge data. We also propose a new format for describing EPL mask data to deal with the huge size of EPL mask data after conversion. The format is called the EPLM format and it contains one main file and multiple subfield files.
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