Reducing Library Characterization Time for Cell-aware Test while Maintaining Test Quality

Cell-aware test (CAT) explicitly targets faults caused by defects inside library cells to improve test quality, compared with conventional automatic test pattern generation (ATPG) approaches, which target faults only at the boundaries of library cells. The CAT methodology consists of two stages. Stage 1, based on dedicated analog simulation, library characterization per cell identifies which cell-level test pattern detects which cell-internal defect; this detection information is encoded in a defect detection matrix (DDM). In Stage 2, with the DDMs as inputs, cell-aware ATPG generates chip-level test patterns per circuit design that is build up of interconnected instances of library cells. This paper focuses on Stage 1, library characterization, as both test quality and cost are determined by the set of cell-internal defects identified and simulated in the CAT tool flow. With the aim to achieve the best test quality, we first propose an approach to identify a comprehensive set, referred to as full set, of potential open- and short-defect locations based on cell layout. However, the full set of defects can be large even for a single cell, making the time cost of the defect simulation in Stage 1 unaffordable. Subsequently, to reduce the simulation time, we collapse the full set to a compact set of defects which serves as input of the defect simulation. The full set is stored for the diagnosis and failure analysis. With inspecting the simulation results, we propose a method to verify the test quality based on the compact set of defects and, if necessary, to compensate the test quality to the same level as that based on the full set of defects. For 351 combinational library cells in Cadence’s GPDK045 45nm library, we simulate only 5.4% defects from the full set to achieve the same test quality based on the full set of defects. In total, the simulation time, via linear extrapolation per cell, would be reduced by 96.4% compared with the time based on the full set of defects

ARMD Workshop on Materials and Methods for Rapid Manufacturing for Commercial and Urban Aviation

This report documents the goals, organization and outcomes of the NASA Aeronautics Research Mission Directorates (ARMD) Materials and Methods for Rapid Manufacturing for Commercial and Urban Aviation Workshop. The workshop began with a series of plenary presentations by leaders in the field of structures and materials, followed by concurrent symposia focused on forecasting the future of various technologies related to rapid manufacturing of metallic materials and polymeric matrix composites, referred to herein as composites. Shortly after the workshop, questionnaires were sent to key workshop participants from the aerospace industry with requests to rank the importance of a series of potential investment areas identified during the workshop. Outcomes from the workshop and subsequent questionnaires are being used as guidance for NASA investments in this important technology area

Anion permselective membrane

The synthesis and fabrication of polymeric anion permselective membranes for redox systems are discussed. Variations of the prime candidate anion membrane formulation to achieve better resistance and/or lower permeability were explored. Processing parameters were evaluated to lower cost and fabricate larger sizes. The processing techniques to produce more membranes per batch were successfully integrated with the fabrication of larger membranes. Membranes of about 107 cm x 51 cm were made in excellent yield. Several measurements were made on the larger sample membranes. Among the data developed were water transport and transference numbers for these prime candidate membranes at 20 C. Other work done on this system included characterization of a number of specimens of candidate membranes which had been returned after service lives of up to sixteen months. Work with new polymer constituents, with new N.P.'s, catalysts and backing fabrics is discussed. Some work was also done to evaluate other proportions of the ingredients of the prime candidate system. The adoption of a flow selectivity test at elevated temperature was explored

Focal Spot, Winter 2005/2006

https://digitalcommons.wustl.edu/focal_spot_archives/1101/thumbnail.jp

Cross-Layer Automated Hardware Design for Accuracy-Configurable Approximate Computing

Approximate Computing trades off computation accuracy against performance or energy efficiency. It is a design paradigm that arose in the last decade as an answer to diminishing returns from Dennard\u27s scaling and a shift in the prominent workloads. A range of modern workloads, categorized mainly as recognition, mining, and synthesis, features an inherent tolerance to approximations. Their characteristics, such as redundancies in their input data and robust-to-noise algorithms, allow them to produce outputs of acceptable quality, despite an approximation in some of their computations. Approximate Computing leverages the application tolerance by relaxing the exactness in computation towards primary design goals of increasing performance or improving energy efficiency. Existing techniques span across the abstraction layers of computer systems where cross-layer techniques are shown to offer a larger design space and yield higher savings. Currently, the majority of the existing work aims at meeting a single accuracy. The extent of approximation tolerance, however, significantly varies with a change in input characteristics and applications. In this dissertation, methods and implementations are presented for cross-layer and automated design of accuracy-configurable Approximate Computing to maximally exploit the performance and energy benefits. In particular, this dissertation addresses the following challenges and introduces novel contributions: A main Approximate Computing category in hardware is to scale either voltage or frequency beyond the safe limits for power or performance benefits, respectively. The rationale is that timing errors would be gradual and for an initial range tolerable. This scaling enables a fine-grain accuracy-configurability by varying the timing error occurrence. However, conventional synthesis tools aim at meeting a single delay for all paths within the circuit. Subsequently, with voltage or frequency scaling, either all paths succeed, or a large number of paths fail simultaneously, with a steep increase in error rate and magnitude. This dissertation presents an automated method for minimizing path delays by individually constraining the primary outputs of combinational circuits. As a result, it reduces the number of failing paths and makes the timing errors significantly more gradual, and also rarer and smaller on average. Additionally, it reveals that delays can be significantly reduced towards the least significant bit (LSB) and allows operating at a higher frequency when small operands are computed. Precision scaling, i.e., reducing the representation of data and its accuracy is widely used in multiple abstraction layers in Approximate Computing. Reducing data precision also reduces the transistor toggles, and therefore the dynamic power consumption. Application and architecture level precision scaling results in using only LSBs of the circuit. Arithmetic circuits often have less complexity and logic depth in LSBs compared to most significant bits (MSB). To take advantage of this circuit property, a delay-altering synthesis methodology is proposed. The method finds energy-optimal delay values under configurable precision usage and assigns them to primary outputs used for different precisions. Thereby, it enables dynamic frequency-precision scalable circuits for energy efficiency. Within the hardware architecture, it is possible to instantiate multiple units with the same functionality with different fixed approximation levels, where each block benefits from having fewer transistors and also synthesis relaxations. These blocks can be selected dynamically and thus allow to configure the accuracy during runtime. Instantiating such approximate blocks can be a lower dynamic power but higher area and leakage cost alternative to the current state-of-the-art gating mechanisms which switch off a group of paths in the circuit to reduce the toggling activity. Jointly, instantiating multiple blocks and gating mechanisms produce a large design space of accuracy-configurable hardware, where energy-optimal solutions require a cross-layer search in architecture and circuit levels. To that end, an approximate hardware synthesis methodology is proposed with joint optimizations in architecture and circuit for dynamic accuracy scaling, and thereby it enables energy vs. area trade-offs