Development and understanding of a plasma-assisted atomic layer deposition process for silicon nitride

In this study we investigated the possibility to replace mercury by metalhalide molecules in the filling of CMH lamps, since mercury is a poisonous substance. Indium iodide was considered a viable alternative, because atomic indium has a high electron-atom collisional cross section.Several lamps were created, in which the indium iodide content was varied, as well as the addition of sodium iodide and dysprosium iodide. The spectra of the lamps were measured in an integrating sphere and their energy balances were determined. The spectra showed that indium iodide emits a broad continuum in the visible and infrared part of the spectrum. There was also a complete absence of ultraviolet radiation. The plasma propertiesin the core of the discharge were determined from the integrating-sphere measurements. Atomic indium lines were used to calculate the core temperature, and a simplified model, developed by Elenbaas, was used to calculate the atomic indium and electron densities. This way, we determined that the broad band continuum was not caused by bremsstrahlung or recombination radiation, but rather by molecular radiation emitted by InI molecules.Varying the indium iodide content in the lamps confirmed that indium iodide increased the resistivity of the lamps and indeed functioned as a buffer gas. However, the application of the Elenbaas model on the integratingsphere measurements suggested that indium iodide led to contraction of the arc column. A seperate side-on setup was created to measure the spectrum as a function of the lateral position in the lamp. A series of measurements over the total lateral width of the lamp were Abel transformed in order to create a radial temperature profile, which showed contraction of the arc. This was also confirmed by photos taken with a cross polarized filter. Contraction by indium iodide can lead to arc instability and limits the use of additives in CMH lamps.A different set of lamps was created that contained tin bromide and tin iodide as an alternative to mercury. These were only measured in the integrating sphere. The spectra of these lamps showed the same trends as the indium iodide lamps. We therefore concluded that neither indium iodide nor tin halides are a suitable alternative to mercury. In this study we investigated the possibility to replace mercury by metalhalide molecules in the filling of CMH lamps, since mercury is a poisonous substance. Indium iodide was considered a viable alternative, because atomic indium has a high electron-atom collisional cross section.Several lamps were created, in which the indium iodide content was varied, as well as the addition of sodium iodide and dysprosium iodide. The spectra of the lamps were measured in an integrating sphere and their energy balances were determined. The spectra showed that indium iodide emits a broad continuum in the visible and infrared part of the spectrum. There was also a complete absence of ultraviolet radiation. The plasma propertiesin the core of the discharge were determined from the integrating-sphere measurements. Atomic indium lines were used to calculate the core temperature, and a simplified model, developed by Elenbaas, was used to calculate the atomic indium and electron densities. This way, we determined that the broad band continuum was not caused by bremsstrahlung or recombination radiation, but rather by molecular radiation emitted by InI molecules.Varying the indium iodide content in the lamps confirmed that indium iodide increased the resistivity of the lamps and indeed functioned as a buffer gas. However, the application of the Elenbaas model on the integratingsphere measurements suggested that indium iodide led to contraction of the arc column. A seperate side-on setup was created to measure the spectrum as a function of the lateral position in the lamp. A series of measurements over the total lateral width of the lamp were Abel transformed in order to create a radial temperature profile, which showed contraction of the arc. This was also confirmed by photos taken with a cross polarized filter. Contraction by indium iodide can lead to arc instability and limits the use of additives in CMH lamps.A different set of lamps was created that contained tin bromide and tin iodide as an alternative to mercury. These were only measured in the integrating sphere. The spectra of these lamps showed the same trends as the indium iodide lamps. We therefore concluded that neither indium iodide nor tin halides are a suitable alternative to mercury

Exploiting partial reconfiguration through PCIe for a microphone array network emulator

The current Microelectromechanical Systems (MEMS) technology enables the deployment of relatively low-cost wireless sensor networks composed of MEMS microphone arrays for accurate sound source localization. However, the evaluation and the selection of the most accurate and power-efficient network’s topology are not trivial when considering dynamic MEMS microphone arrays. Although software simulators are usually considered, they consist of high-computational intensive tasks, which require hours to days to be completed. In this paper, we present an FPGA-based platform to emulate a network of microphone arrays. Our platform provides a controlled simulated acoustic environment, able to evaluate the impact of different network configurations such as the number of microphones per array, the network’s topology, or the used detection method. Data fusion techniques, combining the data collected by each node, are used in this platform. The platform is designed to exploit the FPGA’s partial reconfiguration feature to increase the flexibility of the network emulator as well as to increase performance thanks to the use of the PCI-express high-bandwidth interface. On the one hand, the network emulator presents a higher flexibility by partially reconfiguring the nodes’ architecture in runtime. On the other hand, a set of strategies and heuristics to properly use partial reconfiguration allows the acceleration of the emulation by exploiting the execution parallelism. Several experiments are presented to demonstrate some of the capabilities of our platform and the benefits of using partial reconfiguration

Performance and resource modeling for FPGAs using high-level synthesis tools

High-performance computing with FPGAs is gaining momentum with the advent of sophisticated High-Level Synthesis (HLS) tools. The performance of a design is impacted by the input-output bandwidth, the code optimizations and the resource consumption, making the performance estimation a challenge. This paper proposes a performance model which extends the roofline model to take into account the resource consumption and the parameters used in the HLS tools. A strategy is developed which maximizes the performance and the resource utilization within the area of the FPGA. The model is used to optimize the design exploration of a class of window-based image processing application

Runtime reconfigurable beamforming architecture for real-time sound-source localization

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Efficiency analysis methodology of FPGAs based on lost frequencies, area and cycles

We propose a methodology to study and to quantify efficiency and the impact of overheads on runtime performance. Most work on High-Performance Computing (HPC) for FPGAs only studies runtime performance or cost, while we are interested in how far we are from peak performance and, more importantly, why. The efficiency of runtime performance is defined with respect to the ideal computational runtime in absence of inefficiencies. The analysis of the difference between actual and ideal runtime reveals the overheads and bottlenecks. A formal approach is proposed to decompose the efficiency into three components: frequency, area and cycles. After quantification of the efficiencies, a detailed analysis has to reveal the reasons for the lost frequencies, lost area and lost cycles. We propose a taxonomy of possible causes and practical methods to identify and quantify the overheads. The proposed methodology is applied on a number of use cases to illustrate the methodology. We show the interaction between the three components of efficiency and show how bottlenecks are revealed

Evaluation of classical machine learning techniques towards urban sound recognition embedded systems

Automatic urban sound classification is a desirable capability for urban monitoring systems, allowing real-time monitoring of urban environments and recognition of events. Current embedded systems provide enough computational power to perform real-time urban audio recognition. Using such devices for the edge computation when acting as nodes of Wireless Sensor Networks (WSN) drastically alleviates the required bandwidth consumption. In this paper, we evaluate classical Machine Learning (ML) techniques for urban sound classification on embedded devices with respect to accuracy and execution time. This evaluation provides a real estimation of what can be expected when performing urban sound classification on such constrained devices. In addition, a cascade approach is also proposed to combine ML techniques by exploiting embedded characteristics such as pipeline or multi-thread execution present in current embedded devices. The accuracy of this approach is similar to the traditional solutions, but provides in addition more flexibility to prioritize accuracy or timing

Design exploration and performance strategies towards power-efficient FPGA-based achitectures for sound source localization

Many applications rely on MEMS microphone arrays for locating sound sources prior to their execution. Those applications not only are executed under real-time constraints but also are often embedded on low-power devices. These environments become challenging when increasing the number of microphones or requiring dynamic responses. Field-Programmable Gate Arrays (FPGAs) are usually chosen due to their flexibility and computational power. This work intends to guide the design of reconfigurable acoustic beamforming architectures, which are not only able to accurately determine the sound Direction-Of-Arrival (DoA) but also capable to satisfy the most demanding applications in terms of power efficiency. Design considerations of the required operations performing the sound location are discussed and analysed in order to facilitate the elaboration of reconfigurable acoustic beamforming architectures. Performance strategies are proposed and evaluated based on the characteristics of the presented architecture. This power-efficient architecture is compared to a different architecture prioritizing performance in order to reveal the unavoidable design trade-offs

An empirical Kaiser criterion

In exploratory factor analysis (EFA), most popular methods for dimensionality assessment such as the screeplot, the Kaiser criterion, or—the current gold standard—parallel analysis, are based on eigenvalues of the correlation matrix. To further understanding and development of factor retention methods, results on population and sample eigenvalue distributions are introduced based on random matrix theory and Monte Carlo simulations. These results are used to develop a new factor retention method, the Empirical Kaiser Criterion. The performance of the Empirical Kaiser Criterion and parallel analysis is examined in typical research settings, with multiple scales that are desired to be relatively short, but still reliable. Theoretical and simulation results illustrate that the new Empirical Kaiser Criterion performs as well as parallel analysis in typical research settings with uncorrelated scales, but much better when scales are both correlated and short. We conclude that the Empirical Kaiser Criterion is a powerful and promising factor retention method, because it is based on distribution theory of eigenvalues, shows good performance, is easily visualized and computed, and is useful for power analysis and sample size planning for EF