An FPGA based test bench for non-volatile memory testing
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We present a design framework for the implementation for a Low-Density Parity-Check (LDPC) decoders. We employed a scalable decoding architecture for a certain class of structured LDPC codes.
This viewgraph presentation provides an overview of Field Programmable Gate Arrays (FPGAs), what they are, implementations in space missions, and current available technologies. Single Event Upsets (SEUs) and Single Event Transients (SETs) are discussed in relation to their effects on FPGAs. Testing goals, considerations, and data analysis are reviewed.
This paper describes new software simulation code for predicting single event upset data from measured heavy ion data, using methods, code, and algorithms already reported in the open literature. The measured data that is used to compare against the results of this new simulation code has also been reported in the open literature (R. Koga, et al). The new code is not provided as part of this paper, only the methodology used in generating the code. This paper presents results of basic research, not design-to information, and is representative of other papers reported in the open literature (see paper references). Therefore, the content of this paper is suitable for being made publicly available at the IEEE conference and the resulting IEEE journal.
Progress has been made in a continuing effort to develop a spaceborne computer system for processing readout data from a Fourier-transform infrared (FTIR) spectrometer to reduce the volume of data transmitted to Earth. The approach followed in this effort, oriented toward reducing design time and reducing the size and weight of the spectrometer electronics, has been to exploit the versatility of recently developed hybrid field-programmable gate arrays (FPGAs) to run diverse software on embedded processors while also taking advantage of the reconfigurable hardware resources of the FPGAs.
Techniques and methodologies are developed for assuring and verifying FPGAs that adequately address the increased complexity of the devices required by today'\'s missions.
The Consultative Committee for Space Data Systems (CCSDS) Advanced Orbiting Systems (AOS) space data link protocol provides a framing layer between channel coding such as LDPC (low-density parity-check) and higher-layer link multiplexing protocols such as CCSDS Encapsulation Service, which is described in the following article. Recent advancement in RF modem technology has allowed multi-megabit transmission over space links. With this increase in data rate, the CCSDS AOS protocol implementation needs to be optimized to both reduce energy consumption and operate at a high rate.
Motivation for this work is: (1) Accurately characterize digital signal processor (DSP) core single-event effect (SEE) behavior (2) Test DSP cores across a large frequency range and across various input conditions (3) Isolate SEE analysis to DSP cores alone (4) Interpret SEE analysis in terms of single-event upsets (SEUs) and single-event transients (SETs) (5) Provide flight missions with accurate estimate of DSP core error rates and error signatures.
Multi-rate finite impulse response (MRFIR) filters are among the essential signal-processing components in spaceborne instruments where finite impulse response filters are often used to minimize nonlinear group delay and finite precision effects. Cascaded (multistage) designs of MRFIR filters are further used for large rate change ratio in order to lower the required throughput, while simultaneously achieving comparable or better performance than single-stage designs. Traditional representation and implementation of MRFIR employ polyphase decomposition of the original filter structure, whose main purpose is to compute only the needed output at the lowest possible sampling rate. In this innovation, an alternative representation and implementation technique called TD-MRFIR (Thread Decomposition MRFIR) is presented. The basic idea is to decompose MRFIR into output computational threads, in contrast to a structural decomposition of the original filter as done in the polyphase decomposition. A naive implementation of a decimation filter consisting of a full FIR followed by a downsampling stage is very inefficient, as most of the computations performed by the FIR state are discarded through downsampling. In fact, only 1/M of the total computations are useful (M being the decimation factor). Polyphase decomposition provides an alternative view of decimation filters, where the downsampling occurs before the FIR stage, and the outputs are viewed as the sum of M sub-filters with length of N/M taps. Although this approach leads to more efficient filter designs, in general the implementation is not straightforward if the numbers of multipliers need to be minimized. In TD-MRFIR, each thread represents an instance of the finite convolution required to produce a single output of the MRFIR. The filter is thus viewed as a finite collection of concurrent threads. Each of the threads completes when a convolution result (filter output value) is computed, and activated when the first input of the convolution becomes available. Thus, the new threads get spawned at exactly the rate of N/M, where N is the total number of taps, and M is the decimation factor. Existing threads retire at the same rate of N/M. The implementation of an MRFIR is thus transformed into a problem to statically schedule the minimum number of multipliers such that all threads can be completed on time. Solving the static scheduling problem is rather straightforward if one examines the Thread Decomposition Diagram, which is a table-like diagram that has rows representing computation threads and columns representing time. The control logic of the MRFIR can be implemented using simple counters. Instead of decomposing MRFIRs into subfilters as suggested by polyphase decomposition, the thread decomposition diagrams transform the problem into a familiar one of static scheduling, which can be easily solved as the input rate is constant.
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Commercial-off-the-shelf area array package technologies in high-reliability versions are being considered for NASA electronic systems. These packages are prone to early failure due to the severe mechanical shock and vibration of launch, as well as other less severe conditions, such as mechanical loading during descent, rough terrain mobility, handling, and ground tests. As the density of these packages increases and the size of ball interconnections decrease, susceptibility to mechanical loading and cycling fatigue grows. This report presents a summary of the body of knowledge developed for the evaluation of area array packages and is based on surveys of literature from industry and academia. For high-reliability applications, the limited data that exists will be presented. Most data from industry deals with mechanical fatigue caused by four-point bend tests, as well as from drop tests for hand-held electronics; the most recent data will be presented, along with a brief background of prior literature. Understanding the key design guidelines and failure mechanisms from past tests is critical to developing an approach that will minimize future failures. Additional specific testing enables low-risk insertion of these advanced electronic packages.
Reliability is crucial to safety. Redundancy of important system components greatly enhances reliability and hence safety. Field-Programmable Gate Arrays (FPGAs) are useful for monitoring systems and handling the logic necessary to keep them running with minimal interruption when individual components fail. A complete microcontroller watchdog with logic for failure handling can be implemented in a hardware description language (HDL.). HDL-based designs are vendor-independent and can be used on many FPGAs with low overhead.
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Efficient on-board lossless hyperspectral data compression reduces data volume in order to meet NASA and DoD limited downlink capabilities. The technique also improves signature extraction, object recognition and feature classification capabilities by providing exact reconstructed data on constrained downlink resources. At JPL a novel, adaptive and predictive technique for lossless compression of hyperspectral data was recently developed. This technique uses an adaptive filtering method and achieves a combination of low complexity and compression effectiveness that far exceeds state-of-the-art techniques currently in use. The JPL-developed 'Fast Lossless' algorithm requires no training data or other specific information about the nature of the spectral bands for a fixed instrument dynamic range. It is of low computational complexity and thus well-suited for implementation in hardware.