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This is training presentation for REA (Reading Error Analysis) software. REA is designed for analyzing UGT scope reading errors and for developing reading points optimization algorithms.
The effect of reading error on two hypothetical slope frequency distributions and two slope frequency distributions from actual lunar data in order to ensure that these errors do not cause excessive overestimates of algebraic standard deviations for the slope frequency distributions. The errors introduced are insignificant when the reading error is small and the slope length is large. A method for correcting the errors in slope frequency distributions is presented and applied to 11 distributions obtained from Apollo 15, 16, and 17 panoramic camera photographs and Apollo 16 metric camera photographs.
Results are reported from an extensive investigation into pattern-sensitive soft errors (read disturb errors) in the TCC244 CMOS static RAM chip. The TCC244, also known as the SA2838, is a radiation-hard single-event-upset-resistant 4 x 256 memory chip. This device is being used by the Jet Propulsion Laboratory in the Galileo and Magellan spacecraft, which will have encounters with Jupiter and Venus, respectively. Two aspects of the part's design are shown to result in the occurrence of read disturb errors: the transparence of the signal path from the address pins to the array of cells, and the large resistance in the Vdd and Vss lines of the cells in the center of the array. Probe measurements taken during a read disturb failure illustrate how address skews and the data pattern in the chip combine to produce a bit flip. A capacitive charge pump formed by the individual cell capacitances and the resistance in the supply lines pumps down both the internal cell voltage and the local supply voltage until a bit flip occurs.
We report on TID and SEE tests of multi-level and higher density flash memories. Stand-by currents and functionality tests were used to characterize the response of radiation-induced failures. The radiation-induced failures can be categorized as followings: SEU read errors during irradiation, stuck-bit read errors verified post-irradiation, write errors, erase failures, multiple upsets, and single-event latch up.
A method of reducing errors in noisy magnetic-field measurements involves exploitation of redundancy in the readings of multiple magnetometers in a cluster. By "redundancy"is meant that the readings are not entirely independent of each other because the relationships among the magnetic-field components that one seeks to measure are governed by the fundamental laws of electromagnetism as expressed by Maxwell's equations. Assuming that the magnetometers are located outside a magnetic material, that the magnetic field is steady or quasi-steady, and that there are no electric currents flowing in or near the magnetometers, the applicable Maxwell 's equations are delta x B = 0 and delta(raised dot) B = 0, where B is the magnetic-flux-density vector. By suitable algebraic manipulation, these equations can be shown to impose three independent constraints on the values of the components of B at the various magnetometer positions. In general, the problem of reducing the errors in noisy measurements is one of finding a set of corrected values that minimize an error function. In the present method, the error function is formulated as (1) the sum of squares of the differences between the corrected and noisy measurement values plus (2) a sum of three terms, each comprising the product of a Lagrange multiplier and one of the three constraints. The partial derivatives of the error function with respect to the corrected magnetic-field component values and the Lagrange multipliers are set equal to zero, leading to a set of equations that can be put into matrix.vector form. The matrix can be inverted to solve for a vector that comprises the corrected magnetic-field component values and the Lagrange multipliers.
In this work, we demonstrate SONOS (silicon-oxide-nitrideoxide- silicon) analog memory arrays that are optimized for neural network inference. The devices are fabricated in a 40nm process and operated in the subthreshold regime for in-memory matrix multiplication. Subthreshold operation enables low conductances to be implemented with low error, which matches the typical weight distribution of neural networks, which is heavily skewed toward near-zero values. This leads to high accuracy in the presence of programming errors and process variations. We simulate the end-to-end neural network inference accuracy, accounting for the measured programming error, read noise, and retention loss in a fabricated SONOS array. Evaluated on the ImageNet dataset using ResNet50, the accuracy using a SONOS system is within 2.16% of floating-point accuracy without any retraining. The unique error properties and high On/Off ratio of the SONOS device allow scaling to large arrays without bit slicing, and enable an inference architecture that achieves 20 TOPS/W on ResNet50, a >10× gain in energy efficiency over state-of-the-art digital and analog inference accelerators.
A validation method for the synchronization subsystem of a fault-tolerant computer system is presented. The high reliability requirement of flight-crucial systems precludes the use of most traditional validation methods. The method presented utilizes formal design proof to uncover design and coding errors and experimentation to validate the assumptions of the design proof. The experimental method is described and illustrated by validating the clock synchronization system of the Software Implemented Fault Tolerance computer. The design proof of the algorithm includes a theorem that defines the maximum skew between any two nonfaulty clocks in the system in terms of specific system parameters. Most of these parameters are deterministic. One crucial parameter is the upper bound on the clock read error, which is stochastic. The probability that this upper bound is exceeded is calculated from data obtained by the measurement of system parameters. This probability is then included in a detailed reliability analysis of the system.
The CMS experiment’s High Granularity Calorimeter (HGCAL) upgrade will replace CMS’s existing endcap calorimeters in preparation for the High Luminosity LHC. To effectively use over 6 million channels of this “imaging”calorimeter, CMS has developed two novel Endcap Concentrator (ECON) ASICs to perform data compression/selection on detector. The ECON-D ASIC operates on the 750kHz data path, and the ECON-T ASIC on the 40MHz trigger path. These 65 nm CMOS ASICs are radiation tolerant to 200 Mrad and low power, operating at less than 2.5 mW/channel. The first full-functionality prototype ECONs were produced and characterized in 2021-23, and an initial engineering run was performed in 2024. ECON-D radiation testing for the engineering run revealed that the chip’s internal SRAMs produce intermittent read errors for a non-negligible fraction of chips. Further investigation indicated that the SRAM performance is highly sensitive to the exact parameters of the CMOS fabrication process. To both study this process sensitivity and mitigate SRAM performance issues, twenty ECON wafers were produced in 2025 with a range of doping concentrations designed to tune the underlying transistor threshold voltage by 0%, 5%, 10%, and 15% from nominal. This talk will present first measurements of ECON-D performance, power consumption, and radiation tolerance for these four variations of CMOS process.
The current status and potential applications of an optical-disk buffer (ODB) memory system being developed by an interagency consortium including NASA and the USAF are reviewed. The design goals for the ODB include usable capacity 1 Tb, maximum data rate 1.6 Gb/s, read error rate less than 10 to the -12th, time to initial access less than 100 ms, and unlimited read/write cycles. Present efforts focus on a brassboard ODB which employs 12 14-inch magnetooptic disks and 24 nine-diode read/write heads. A typical space application of an optical disk mass memory system (ODMMS) is discussed: as communications buffer, temporary storage, and/or multiuser I/O buffer for data management on the Space Station Earth Observing System. Environmental, operational, system-architecture, and functional-separation factors; critical design issues; and standardization questions for spaceborne ODMMSs are examined in detail.
The XQR18V04 was evaluated for single event upset rates using proton and heavy ions. The PROM was demonstrated to be immune to latch-up, as well as to static upset in the flash memory cells, to an LET > 125 MeV/mg/cmz (effective). The PROM was also tested in a dynamic mode, which revealed three distinct error modes: Read Bit Errors, Address Errors, and a Single Event Functional Interrupt (SEW which affected the data output drivers. Saturation cross-sections, and onset thresholds, for these errorinodes were measured at the heavy ion facility at Texas A&M University, and the proton facility at UC Davis. Additional testing was performed at UC Davis and the Cobalt 60 source at McClellan Air Force Base to examine the effect to TID life as a function of power biasing. The PROM demonstrated a 100% improvement in total TID life with an 84% percent decrease in device usage.
We report on SEE and TID tests of highly scaled Samsung 2Gbits flash memories. Both in-situ and biased interval irradiations were used to characterize the response of the total accumulated dose failures. The radiation-induced failures can be categorized as followings: single event upset (SEU) read errors in biased and unbiased modes, write errors, and single-event-functional-interrupt (SEFI) failures.
A method allows combining the functions of a heater and a thermometer in a single device, a thermistor, with minimal temperature read errors. Because thermistors typically have a much smaller thermal mass than the objects they monitor, the thermal time to equilibrate the thermometer to the temperature of the object is typically much shorter than the thermal time of the object to change its temperature in response to an external perturbation.
Here, we have evaluated the Read-Retry (RR) functionality of the 3-D NAND chip of multilevel-cell (MLC) configuration after total ionization dose (TID) exposure. The RR function is typically offered in the high-density state-of-the-art NAND memory chips to recover data once the default memory read method fails to correct data with error correction codes (ECCs). In this work, we have applied the RR method on the irradiated 3-D NAND chip that was exposed with a Co-60 gamma-ray source for TID up to 50 krad (Si). Based on our experimental evaluation results, we have proposed an algorithm to efficiently implement the RR method to extend the radiation tolerance of the NAND memory chip. Our experimental evaluation shows that the RR method coupled with ECC can ensure data integrity of MLC 3-D NAND for TID up to 50 krad (Si).
With the increasing packing densities in VLSI technology, Single Event Upsets (SEU) due to cosmic radiations are becoming more of a critical issue in the design of space avionics systems. In this paper, a method is introduced to compute the fault (mishap) probability for a computer memory of size M words. It is assumed that a Hamming code is used for each word to provide single error correction. It is also assumed that every time a memory location is read, single errors are corrected. Memory is read randomly whose distribution is assumed to be known. In such a scenario, a mishap is defined as two SEU's corrupting the same memory location prior to a read. The paper introduces a method to compute the overall mishap probability for the entire memory for a mission duration of T hours.
Often there are errors when reading data from computer memory. To detect and correct these errors, there are multiple types of error correction codes. Disclosed is an error correction architecture that creates a codeword having a data portion and an error correction code portion. Swizzling rearranges the order of bits and distributes the bits among different codewords. Because the data is redistributed, a potential memory error of up to N contiguous bits, where N for example equals 2 times the number of codewords swizzled together, only affects up to, at most, two bits per swizzled codeword. This keeps the error within the error detecting capabilities of the error correction architecture. Furthermore, this can allow improved error correction and detection without requiring a change to error correcting code generators and checkers.
Often there are errors when reading data from computer memory. To detect and correct these errors, there are multiple types of error correction codes. Disclosed is an error correction architecture that creates a codeword having a data portion and an error correction code portion. Swizzling rearranges the order of bits and distributes the bits among different codewords. Because the data is redistributed, a potential memory error of up to N contiguous bits, where N for example equals 2 times the number of codewords swizzled together, only affects up to, at most, two bits per swizzled codeword. This keeps the error within the error detecting capabilities of the error correction architecture. Furthermore, this can allow improved error correction and detection without requiring a change to error correcting code generators and checkers.
Abstract Genotyping‐by‐sequencing (GBS) is a widely used strategy for obtaining large numbers of genetic markers in model and non‐model organisms. In crop plants, GBS‐derived marker datasets are frequently used to perform quantitative trait locus (QTL) mapping. In some plant species, however, high heterozygosity and complex genome structure mean that researchers must use care in handling GBS data to conduct QTL mapping most effectively. Such outbred crops include most of the perennial grass and tree species used for bioenergy. To identify strategies for increasing accuracy and precision of QTL mapping using GBS data in outbred crops, we conducted an empirical study of SNP‐calling and genetic map‐building pipeline parameters in a Miscanthus sinensis population, and a complementary simulation study to estimate the relationship between genome‐wide error rate, read depth, and marker number. The bioenergy grass Miscanthus is an obligate outcrossing species with a recent (diploidized) whole‐genome duplication. For the study of empirical M. sinensis data, we compared two SNP‐calling methods (one non‐reference‐based and one reference‐based), a series of depth filters (12×, 20×, 30×, and 40×) and two map‐construction methods (i.e., marker ordering: linkage‐only and order‐corrected based on a reference genome). We found that correcting the order of markers on a linkage map by using a high‐quality reference genome improved QTL precision (shorter confidence intervals). For typical GBS datasets of between 1000 and 5000 markers to build a genetic map for biparental populations, a depth filter set at 30× to 40× applied to outbred populations provided a genome‐wide genotype‐calling error rate of less than 1%, improved accuracy of QTL point estimates and minimized type I errors for identifying QTL. Based on these results, we recommend using a reference genome to correct the marker order of genetic maps and a robust genotype depth filter to improve QTL mapping for outbred crops.
With global warming at the rate of 10 mK/yr, it is important to at least characterize any trend in the AIRS data, which may impact the use of AIRS data for climate change research. We evaluated the stability of the AIRS v5 calibration for seven atmospheric window channels between 2002 and 2018 under tropical ocean clear conditions. Trends for the channels between 961, 1128 and 1231 cm-1 channels are typically +3 mK/yr; for 790 and 901 cm-1 the trend is 6 mK/yr, i.e. the observations are increasingly getting warmer than expected. The trends are day/night consistent. The trend for the 2508 and 2616 cm-1 channels is close to 10 mK/yr at night, but closer to 6 mK/yr during the day. On an absolute scale these trends are small, but not when viewed in the context of global warming at a 10 mK/yr rate. While the warming trends are consistent with increased scattering from the scan mirrors, which create an error in reading the Onboard Blackbody Calibration, the resulting changes in the gain are a factor of about five larger than observed changes in the gain. The effects of scattering due to scan mirror contamination are evident at extremely cold temperatures, but scattering does not produce the observed warming at warm temperatures. It is possible that much of the observed warming in the AIRS window channels is a geophysical effect related to the warming of the oceans, resulting in a shift in the diurnal cycle and skin effect correction. This requires more careful evaluation.