Well designed redundant via-aware standard cells (SCs) can increase the redundant via1 insertion rate in cell-based designs. However, in conventional methods, manual- and visual-based checks are required to locate pins and tune the geometries of layouts. These tasks can be very time consuming and unreliable. In this work, an O(Nlog N) redundant via-aware standard cell optimization scheme is developed. The proposed method is an efficient layout check and optimization scheme that considers various redundant via configurations including the double-via and rectangle-via to shorten the design time for standard cells. The optimized SCs effectively increase the redundant via insertion rate, and in particular the insertion rate of via1 for both concurrent routing and post-layout optimization. Furthermore, an automatic layout checker and optimizer are more efficient in identifying expandable metal 1 pins in libraries that contain numerous cells than are conventional visual check and manual optimization. Therefore, the proposed scheme not only solves the problem of a low via1 insertion rate in nanometer regimes, but also provides an efficient layout optimizer for designing standard cells. Experimental results indicate that the optimized standard cells increase the double-via1 insertion rates by 21.9%.

Due to the increasing need for low-power circuits in mobile applications, numerous leakage and performance optimization techniques are being used in modern ICs. In the present paper, we propose a novel transistor-level technique to reduce leakage current while maintaining drive current. By slightly increasing the channel length at the edge of a device that exploits the edge effect, a leakage-optimized transistor can be produced. By using TCAD simulations, we analyze edge-length-biased transistors and then propose the optimal transistor shape for minimizing Ioff with the same or higher Ion current. Results show that by replacing all standard cells with their leakage-optimized counterparts, we can save up to 17% of the leakage in average for a set of benchmark circuits.

Current sources are essential components for analog circuit designs, the mismatch of which causes the significant degradation of the circuit performance. This paper addresses the mismatch model of CMOS current sources, unlike the conventional modeling, focusing on the layout- and λ-dependency of the process variation, where λ is the output conductance parameter. To make it clear what variation parameter influences the mismatch, we implemented a test chip on 90 nm process technology, where we can collect the characteristics variation data for MOSFETs of various layouts. The test chip also includes D/A converters to check the differential non-linearity (DNL) caused by the mismatch of current sources when behaving as a DAC. Identifying the variation and the circuit-level errors in the measured DNLs, we reveal that our model can more accurately account for the current variation compared to the conventional mismatch model.

Digital RF solutions have been shown to be advantageous in various design aspects, such as accurate modeling, design reuse, and scaling when migrating to the next CMOS process node. Consequently, the majority of new low-cost and feature cell phones are now based on this approach. However, another equally important aspect of this approach to wireless transceiver SoC design, which is instrumental in allowing fast and low-cost productization, is in creating the inherent capability to assess performance and allow for low-cost built-in calibration and compensation, as well as characterization and final-testing. These internal capabilities can often rely solely on the SoCs existing processing resources, representing a zero cost adder, requiring only the development of the appropriate algorithms. This paper presents various examples of built-in measurements that have been demonstrated in wireless transceivers offered by Texas Instruments in recent years, based on the digital-RF processor (DRPTM) technology, and highlights the importance of the various types presented; built-in self-calibration and compensation, built-in self-characterization, and built-in self-testing (BiST). The accompanying statistical approach to the design and productization of such products is also discussed, and fundamental terms related with these, such as 'soft specifications', are defined.

The long-standing problem of predicting circuit performance variations without a huge number of statistical investigations is demonstrated to be solvable by a surface-potential-based MOSFET model. Direct connection of model parameters to physical device parameters reflecting process variations and the reduced number of model parameters are the enabling key model properties. It has been proven that the surface-potential-based model HiSIM2 is capable of reproducing measured I-V and its derivatives' variations with those of device/process related model parameters. When used to predict 51-stage ring oscillator frequency variation including both inter- and intra-chip variation, it reproduces measurements with shortened simulation time.

The increase in the time required for data processing, mask drawing, and inspection of photomask, has led to substantial increase in mask manufacturing cost. This has become one of the major challenges in the semiconductor industry. 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 mask patterns from the view point of the design side. As a result, we can reduce mask writing time and mask inspection time. Our objective is to build efficient data flow conversion system from DI to MDR. In this paper we introduce the idea of MDR and the software system that we built for DI extraction. Then we show the experimental results with actual chip data. Lastly we will discuss related issues and their solutions.

In this paper, the vibration characteristics of stapes, driven by the implanted differential floating mass transducer (DFMT) in the human middle ear, are analyzed by using an electrical model. The electrical model has been simulated by using the PSpice, in which the simulated results are compared with the experimental results by using the fabricated DFMT and the human temporal bones.

This paper studies the impact of dummy fill for chemical mechanical polishing (CMP)-induced capacitance variation on buffer insertion based on a virtual CMP fill estimation model. Compared with existing methods, our algorithm is more feasible by performing buffer insertion not in post-process but during early physical design. Our contributions are threefold. First, we introduce an improved fast dummy fill amount estimation algorithm based on [4], and use some speedup techniques (tile merging, fill factor and amount assigning) for early estimation. Second, based on some reasonable assumptions, we present an optimum virtual dummy fill method to estimate dummy position and the effect on the interconnect capacitance. Then the dummy fill estimation model was verified by our experiments. Third, we use this model in early buffer insertion after layer assignment considering the effects of dummy fill. Experimental results verified the necessity of early dummy fill estimation and the validity of our algorithm. Buffer insertion considering dummy fill during early physical design is necessary and our algorithm is promising.

We focus our attention on the layout dependent Across Chip Linewidth Variability (ACLV) of gate-forming poly-silicon patterns as a measure for manufacturability, which is a major contributor of systematic gate-length variation. First, we study the ACLV of standard cell layouts by lithography simulation. Then, we introduce regularity in gate-forming poly-silicon patterns and how it improves the ACLV and also how it incurs area-overhead. According to the investigation, we propose two design guidelines for standard-cell layout that can reduce ACLV with reasonable area overhead. Those guidelines include on-grid fixed-pitch layout with dummy-poly insertion and stretched gate-poly extension. Design experiments assuming a 65 nm process technology indicate that a D-FF designed with the first guideline reduces ACLV by 35% with 14% area overhead and the second guideline reduces ACLV by 75% with 29% area overhead at the best focus condition. Under defocus conditions, both layouts exhibit stable characteristics whereas the variability of conventional layout grows rapidly as the level of defocus increases. Circuit-level lithography simulation over benchmark circuits also supports that the proposed guidelines considerably reduces the amount of gate length variation.

The advanced-DFM (Design For Manufacturability) RAM provides the solution for the limitation of SRAM voltage scaling down and the countermeasure of the process fluctuations. The characteristics of this RAM are the voltage scalability (@0.6 V operation) with wide operating margin and the reliability of long data retention time. The memory cell consists of 2 Cell/bit with the complementary dynamic memory operation and has the 1 Cell/bit test mode for the accelerated screening against the marginal cells. The GND bitline pre-charge sensing scheme and SSW (Sense Synchronized Write) peripheral circuit technologies are also adopted for the low voltage and DFV (Dynamic Frequency and Voltage) controllable SoC which will be strongly required from the many kinds of applications. This RAM supports the DFM functions with both good cell/bit for advanced process technologies and the voltage scalable SoC memory platform.

We have fabricated a LUT-based FPGA device with functionalities measuring within-die variations in a 90 nm process. Variations are measured using ring oscillators implemented as a configuration of the FPGA. Random variations are dominant in a 4848 configurable array laid out in a 3 mm3 mm square region. It has a functionality to measure delays on actual signal paths between flip flops by providing two clock pulses. Measured variations are used to maximize the operating frequency of each device by choosing the optimal paths. Optimizations of routing paths using a simple model circuit reveals that performance of the circuit is enhanced by 2.88% in average and a maximum of 9.34%.

With the recent advance of process technology shrinking, process parameter variation has become one of the major issues in SoC designs, especially for timing convergence. Recently, Statistical Static Timing Analysis (SSTA) has been proposed as a promising solution to consider the process parameter variation but it has not been widely used yet. For estimating the delay yield, designers have to know and understand the accuracy of SSTA. However, the accuracy has not been thoroughly studied from a practical point of view. This paper proposes two metrics to measure the pessimism/optimism of SSTA; the first corresponds to yield estimation error, and the second examines delay estimation error. We apply the metrics for a problem which has been widely discussed in SSTA community, that is, normal-distribution approximation of max operation. We also apply the proposed metrics for benchmark circuits and discuss about a potential problem originating from normal-distribution approximation. Our metrics indicate that the appropriateness of the approximation depends on not only given input distributions but also the target yield of the product, which is an important message for SSTA users.

In the move toward higher clock rates and advanced process technologies, designers of the latest electronic products are finding increasing silicon failure with respect to noise. On the other hand, the minimum dimension of patterns on LSIs is much smaller than the wavelength of exposure, making it difficult for LSI manufacturers to obtain high yield. In this paper, we present a solution to reduce power-supply noise in LSI microchips. The proposed design methodology also considers design for manufacturability (DFM) at the same time as power integrity. The method was successfully applied to the design of a system-on-chip (SOC), achieving a 13.1-13.2% noise reduction in power-supply voltage and uniformity of pattern density for chemical mechanical polishing (CMP).

It is a critical design process to estimate the fractional errors of the Synthetic Aperture Radar (SAR) processor before implementation. The contribution of this paper is to identify the chief sources and types and to suggest an estimation technique for overall fractional errors of the space-based SAR processor using Range-Doppler Algorithm (RDA). Also, simulation is performed to the Experimental-SAR (E-SAR) processor to examine the practicability and efficiency of the technique, the results are discussed, and the solutions for problems are recommended. Therefore, this technique can be used to estimate the fractional errors of the space-based SAR processor using RDA.

This paper proposes a nonlinear distortion suppression scheme for optical direct FM Radio-on-Fiber system. This scheme uses the interaction between the nonlinearities of DFM-LD and OFD to suppress a 3rd order intermodulation distortion. We theoretically analyze the carrier to noise-plus-distortion ratio (CNDR) and show a controlling method in the MZI type OFD to realize the proposed suppression scheme.

This paper proposes a nonlinear distortion suppression scheme for optical direct FM Radio-on-Fiber system. This scheme uses the interaction between the nonlinearities of DFM-LD and OFD to suppress a 3rd order intermodulation distortion. We theoretically analyze the carrier to noise-plus-distortion ratio (CNDR) and show a controlling method in the MZI type OFD to realize the proposed suppression scheme.