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Down to the wire -- requirements for nanometer design implementation |
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Ping Chao and Lavi Lev
(08/15/2002 5:13 PM EDT) URL: http://www.eetimes.com/showArticle.jhtml?articleID=16505500 |
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1 Introduction
Implementing nanometer-scale ICs begins and ends with wires. Wires are so dominant that little is known about a design's performance or manufacturability without them. In fact, nanometer design strategies that are not clearly focused on rapid wire creation, optimization, and analysis are destined to fail.
This paper describes the requirements for an effective, reliable IC implementation platform for the 90 nm process node and beyond. It begins with a description of the central role wires play in nanometer design and why traditional linear design flows are insufficient. It then describes a new continuous convergence methodology, which has proven highly valuable at 0.13 micron and will be absolutely necessary at 90 nm.
Next, the paper describes the key implementation, analysis, and database technologies needed to enable this methodology. Implementing nanometer designs requires nanometer routers that optimize wire creation for both performance and manufacturability. Verifying nanometer designs requires nanometer analysis tools that accurately model physical effects as they would occur in the target silicon. Efficiently representing these designs-most of which will be large digital designs with critical analog circuitry-requires unified nanometer databases with massive capacity and efficient extensibility.
Wires must be the centerpiece of any nanometer methodology. Without such a methodology, design teams will not be able to create massively complex nanometer ICs in a timeframe of relevance.
2 Wiring dominates nanometer design
In nanometer design, wiring delay accounts for the vast majority of overall delay. It is well known that delay has been shifting from gates to wires for quite some time. As shown in Figure 1, wiring delay exceeds gate delay at 0.18 micron and below in aluminum processes, and at 0.13 micron and below in copper. By 90 nm, wiring delay will account for some 75% of the overall delay. As a result, design teams need to shift their focus from logic optimization to wire optimization.
![]() Figure 1: Wire and gate delay in Al and Cu
2.1 The changing nature of delay
2.1.1 Cross coupling
As process geometries decrease, the primary capacitive coupling on a given wire moves to its neighboring wires. Capacitance depends on the local wire geometry and, in many cases, to the actual signals on neighboring wires. As an example, Figure 2 shows delay variation at 0.18 micron due to capacitive coupling for signals at 1X and 2X grid spacings. The variation is up to +/-30% for 1 mm wires and +80%/-60% for 3 mm wires.
![]() Figure 2: Crosstalk introduces substantial delay variation
At 0.18 micron, cross coupling affects only high-performance designs significantly. By 90 nm, it will significantly affect all designs. Since capacitance is no longer strictly proportional to wire length at nanometer geometries, detailed routing is required for accurate timing analysis.
2.1.2 IR drop
2.2 Nanometer technical issues
Table 1 -- Critical nanometer design issues
The most striking feature of any list of critical nanometer design issues is the number of issues that relate to wiring. At nanometer geometries, wiring dominates nearly all aspects of IC implementation-including design time, performance, area, and manufacturability.
3 Continuous convergence methodology
The critical role wires play at the 90 nm process node and beyond makes traditional linear design flows ineffective. Nanometer design requires a completely different design strategy-continuous convergence.
3.1 The need for a design strategy
As the percentage of delay in the wires increases, linear flows become more unpredictable and inefficient. At 0.18 micron, performance is unknown prior to placement. Using floorplanning and physical synthesis tools, designers can iterate at the placement level to try to find a feasible solution (see Figure 3). When there is no feasible solution, they must go all the way back to change the architecture or logic. The high probability of long iterations greatly reduces predictability, while the iterations themselves greatly reduce efficiency. At 90 nm, performance is unknown prior to detailed routing; this introduces more iterations and longer iterations-and much less predictability and efficiency.
![]() Figure 3: Optimization and analysis iterations by process node
With timing based primarily on wires in nanometer designs, design teams must use methodologies that both generate wires as soon as possible ("time-to-wire") and minimize full-chip iteration time. Time-to-wire and full-chip iteration time will be the critical metrics for design predictability and efficiency in nanometer design.
3.1 Floorplanning is insufficient
3.1.2 Physical synthesis is insufficient
Despite early market predictions that physical synthesis would replace logic synthesis, design teams use it only to re-optimize gate-level blocks that do not meet timing. In nanometer design, design teams will use physical synthesis only on those blocks that full-chip detailed routing identifies as not meeting timing. At that point, physical synthesis serves as a valuable optimization engine to provide routing with a better starting point for wire optimization. However, the wires themselves-not the logic or placement-will dictate performance.
3.2 Nanometer design methodology: Continuous convergence
3.2.1 A virtual tapeout every day
Design teams that use continuous convergence often standardize on a one-day turnaround-in essence, performing a virtual tapeout every day. Thus, every day they see predictable, measurable, systematic progress toward their goal of silicon closure and final tapeout (see Figure 4).
![]() Figure 4: Continuous convergence methodology
3.2.2 Silicon virtual prototype
The SVP must support clock structures, power grid, top-level interconnect, and other characteristics of the tapeout design. It must account for all relevant overhead in order to represent a known, physically feasible solution which can guide decisions such as timing-budget and pin assignments-a fully detailed layout with wiring is the only way to guarantee feasible budgets and assignments.
![]() Figure 5: An SVP can serve as a design cockpit
An SVP can serve as a universal cockpit for all tools and functions, combining all aspects of implementation and analysis within a single full-chip environment (see Figure 5). This environment can include implementation functions-floorplanning, placement, physical synthesis, routing, clock-tree synthesis, and power planning-and analysis functions-timing, signal integrity, routability, and power analysis.
3.3 Hierarchical and high-capacity flat support
Continuous convergence must support hierarchical and high-capacity flat designs. Tool capacity is critical in either case. Nanometer tools will need massive capacity and performance compared to today's standards. Many current IC implementation tools have practical capacities on the order of 1M gates. Yet some tools have a much less useful capacity, requiring otherwise unnecessary hierarchy. This hierarchy can introduce substantial overhead, such as the need for budgets and constraints, and reduce overall optimization opportunities. It also adds risk-a single incorrect time-budget value can make an otherwise feasible design impossible.
Obviously, tools should not constrain designers unnecessarily. All nanometer tools should have the capacity and performance to handle 10M gate designs flat, an order-of-magnitude increase over today's nominal capabilities. This is achievable through a number of means including improved algorithms and data structures, and using multiple processors. A 10M gate useful capacity provides design teams with much more freedom to choose when and how to utilize hierarchy.
4 Nanometer routing requirements
Full-chip detailed routing is the first step in assessing a design's initial performance. It is also the last step in optimizing the design to meet all of its performance and manufacturing requirements. Nanometer design demands a new type of router that is physics-aware, manufacturing-aware, and has massive capacity and performance.
4.1 Physics-aware routing
4.2 Manufacturing-aware routing
Most design teams run into manufacturability issues for the first time at 0.13 micron. Processes using copper wiring, chemical-mechanical polishing (CMP), and subwavelength lithography lead to exceedingly complex and arcane design rules. Antenna rules, to take one example, require careful handling to avoid via proliferation and minimize wire lengths. Furthermore, foundries continue to change the design rules long after the introduction of a new process in order to optimize time-to-silicon production.
Nanometer routers must explicitly provide for variable width and variable spacing, and they must be capable of adapting to the requirements of copper, multiple vias, OPC, phase-shift masking (PSM), and CMP. Beyond 90 nm, routers will have to optimize the wiring specifically to facilitate manufacturing processes. Nanometer designs will challenge any router that is not designed specifically to account for these advanced process considerations.
4.3 Massive routing capacity and performance
The router must be tightly coupled with, and have control over, almost every aspect of the physical realization of the chip, including:
Nanometer routers must have concurrent access to full parasitic extraction, full-chip static timing analysis (STA), and signal integrity analysis, using these results to guide and to modify routes on-the-fly. High-end design teams must account for the complex interactions between signal, power, and clock routing. For instance, in 90 nm high-performance designs high-speed clock routing must be tightly controlled using techniques such as shielding, track assignment, and topology control. Routing must be integrated with automatic clock tree synthesis and clock timing analysis.
Performing the above, along with supporting variable wire widths and spacings, requires massive capacity and performance. A meaningful benchmark is the ability to route a 10M gate design overnight. Doing so is likely to require multithreading and multiprocessing in order to utilize all computational resources available for the task.
5 Nanometer physical analysis requirements
Every process node change introduces new challenges. The simultaneous move to copper at 90 nm causes more, and more difficult, problems than usual. These problems make it all the more difficult to get accurate analysis information. Successful nanometer design requires the use of nanometer-scale analysis tools throughout the design process. These tools should not only identify problems, but also provide guidance for addressing them.
5.1 What you see is not what you get
With the right analysis information, design teams can also get significantly more performance out of a given process technology. Microprocessor design teams using full-custom techniques often achieve 7x to 10x higher frequencies at given process nodes than typical ASIC design teams using semi-custom techniques. A considerable part of the difference is based on having accurate physical analysis information, which enables designers to cut margins tremendously. As a result, they can gain performance at a given process node or reduce the cost per chip by using a less expensive process node.
5.2 Parasitic extraction
From a methodology point of view, getting the most out of the silicon requires utilizing the most accurate physical information necessary during every design iteration. During early design iterations, turnaround time is at a premium. Later in the design cycle, accuracy is most critical. Using a less accurate extractor to speed iterations can mean increased margin and increased timing closure risk. An extractor should be fast enough to enable designers to complete block iterations within 1-2 hours. It should also complete a full-chip extraction overnight, using multiprocessor computers if necessary to do so.
5.3 Delay calculation
![]() Figure 6: Nanometer delay calculation with SI and IR drop
Hierarchical delay calculation is also important in nanometer design. Simplistic, conservative timing models at hierarchical boundaries increase margins. Delay calculations must correctly model paths that cross hierarchical boundaries to maintain accuracy.
5.4 Signal electromigration
Signal EM becomes more of a problem as wires get smaller and designers are forced to push more current through them to meet performance. Place-and-route tools that create large drivers on nets to meet timing can create EM problems throughout a massive chip-problems that design teams do not even know about. Nanometer physical analysis must identify EM problems before they occur in silicon, including AC-induced EM due to high-frequency signals-generally those over 300 MHz and those with many hazard-as well as DC-induced EM due to large unidirectional current flow.
5.5 Power grid analysis
Accurate power-grid analysis requires modeling design activity that is representative of the actual signal transitions. It is getting extremely difficult to provide adequate vector sets for many complex designs. Power-grid analysis tools should be able to use probabilistic techniques which can provide accuracy that neither static methods nor vector-based methods can match for a growing number of designs. For accuracy, power-grid analysis must also take into consideration manufacturing techniques such as OPC and PSM, necessitating the ongoing model calibration to foundry silicon.
5.6 Inductance
6 Nanometer design database requirements
The right database is more important than ever in nanometer design, with its massively complex chips, elaborate physical requirements, arcane manufacturing requirements, and all that is still unknown. The majority of nanometer designs will be digital/mixed-signal ICs (i.e., large digital designs with critical analog circuitry) making it particularly important to that the database support a unified data model.
There was much debate in the early 1980s over the then-novel concept of combining geometric data and its associated connectivity data in a single database. Yet taking that step enabled some of our most significant algorithms advances including connectivity-based editing, place-and-route, physical synthesis, and efficient physical verification. The time is right for a next-generation unified database.
6.1 Unified data model
A unified database enables all design tools to operate off of a common representation, eliminating time-consuming and error-prone file transfers. Each application can focus on only the relevant parts of the database-as developers add new data types, only those applications that need the new data need to change. With today's interchange formats, every application must understand, store, and output all information contained in the format-often resulting in information loss. A unified database eliminates such loss as each tool reads, reinterprets, transforms, and writes it.
![]() Figure 7: Nanometer database with unified data model
A unified database allows for new algorithms that use design intent currently only accessible to specific tools. For example, an OPC creation tool can examine the slack on each signal before selecting which correction to apply, reducing mask complexity and cost. Another example includes intelligent mixed-signal design partitioning, simulation, and analysis.
6.2 Key features
6.3 Massive database capacity and performance
High database performance enables many tools to operate directly off the database, saving application development time. While some tools will use their own proprietary data structures for runtime efficiency, the persistent repository will remain the centralized database. If the database also has an appropriate extensibility model, fewer and fewer applications will duplicate structures, such as the netlist, that already exist in the database.
6.4 Extensibility and openness
With appropriate extensibility, application developers-including in-house and third-party tool developer-can write efficient algorithms to manipulate and analyze the data they need precisely at full speed. Extensions should be available permanently to enable other tools to use them, or temporarily to serve as a coherent high-performance cache. In-memory coherence makes it possible to write tools built from cooperating components that are incremental in nature, to use lazy evaluation techniques, and to provide application-level toolkits that allow rapid new tool evolution and construction.
Nanometer databases should be open, which includes having an open application programming interface (API), open source code, and a community-based oversight committee. Openness is not a technical requirement per se, but it directly facilitates a technically superior implementation that advances rapidly. It also mitigates design team risk by enabling native third-party and in-house application development.
6.5 The future - connecting with manufacturing
7 Conclusions
Wires dominate performance and manufacturability at 90 nm and below, making traditional linear flows obsolete. Wires are so important that performance analysis or optimization without detailed routing information is essentially meaningless.
Successful nanometer physical IC design requires wire-centric strategies, such as the continuous convergence methodology presented in this paper. It is a proven methodology that minimizes both time-to-wires and full-chip iteration time. Design teams that use continuous convergence see predictable, measurable, systematic progress toward their goal of silicon closure and final tapeout.
Nanometer success also requires a new set of implementation, analysis, and database technologies. Nanometer routers must be physics aware, taking physical effects such as SI into consideration on-the-fly. They must also be manufacturing-aware, with capabilities such as variable-spacing and variable-width routes to support copper, CMP, and subwavelength processes. Nanometer physical analysis must represent the target silicon accurately.
Silicon integrity and IR drop have become first-order timing effects, and EM is an issue for signals as well as the power grid. An extensible, unified database provides the foundation for nanometer design, especially since most designs will be digital/mixed-signal. It needs to support a rich set of objects, attributes, and relationships. Perhaps more importantly, it must support extensibility with native performance. The database and all nanometer tools should support hierarchy elegantly and handle 10M gate designs efficiently.
Nanometer design implementation places extraordinary demands on design teams. Those that embrace wire-centric design strategies such as continuous convergence will thrive at the expense of those that do not.
Appendix: Critical nanometer design technical issues
Below are descriptions of 10 top technical issues associated with nanometer design.
Table 1 -- Critical nanometer design issues
1 Design size and complexity
2 Timing based on signal integrity
3 IR drop (power grid design)
4 Crosstalk and inductance
5 Electromigration
6 Digital-analog integration
7 Power consumption
8 System signal transmission
9 Manufacturing rules
10 Yield optimization
Lavi Lev is executive vice president and general manager for IC solutions at Cadence Design Systems. Before joining Cadence, Lavi was Senior Vice President of Engineering at MIPS Technologies. He has also led engineering teams at Silicon Graphics, MicroUnity Systems, Sun Microsystems, Intel Corporation, and National Semiconductor. With 20 years experience in the semiconductor industry and over 15 patents, Lavi has developed microprocessor and system-on-a-chip solutions for supercomputers, workstations, PCs, and consumer devices. He holds a bachelor of science degree in electrical engineering from Technion, Israel Institute of Technology.
Ping Chao is senior vice president and general manager for digital IC solutions at Cadence Design Systems. Ping is a co-founder of Cadence and has an extensive career in the EDA industry and electronic design. He founded and held executive management positions in three successful EDA start-up companies-ECAD, PiE Design Systems and Silicon Perspective-taking them through IPOs/acquisitions and growth to market leadership positions. He earned a B.S.E.E. degree from National Chiao-Tung University, Taiwan, and a M.S.E.E./C.S. degree from the University of California, Berkeley.
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