Genomic prediction of starch content and chipping quality in tetraploid potato using genotyping-by-sequencing

peer-reviewedGenomic prediction models for starch content and chipping quality show promising results, suggesting that genomic selection is a feasible breeding strategy in tetraploid potato. Genomic selection uses genome-wide molecular markers to predict performance of individuals and allows selections in the absence of direct phenotyping. It is regarded as a useful tool to accelerate genetic gain in breeding programs, and is becoming increasingly viable for crops as genotyping costs continue to fall. In this study, we have generated genomic prediction models for starch content and chipping quality in tetraploid potato to facilitate varietal development. Chipping quality was evaluated as the colour of a potato chip after frying following cold induced sweetening. We used genotyping-by-sequencing to genotype 762 offspring, derived from a population generated from biparental crosses of 18 tetraploid parents. Additionally, 74 breeding clones were genotyped, representing a test panel for model validation. We generated genomic prediction models from 171,859 single-nucleotide polymorphisms to calculate genomic estimated breeding values. Cross-validated prediction correlations of 0.56 and 0.73 were obtained within the training population for starch content and chipping quality, respectively, while correlations were lower when predicting performance in the test panel, at 0.30-0.31 and 0.42-0.43, respectively. Predictions in the test panel were slightly improved when including representatives from the test panel in the training population but worsened when preceded by marker selection. Our results suggest that genomic prediction is feasible, however, the extremely high allelic diversity of tetraploid potato necessitates large training populations to efficiently capture the genetic diversity of elite potato germplasm and enable accurate prediction across the entire spectrum of elite potatoes. Nonetheless, our results demonstrate that GS is a promising breeding strategy for tetraploid potato.The Danish Council of Strategic Researc

Miniaturized Pumps and Gauges for Ultra-High Vacuum Microsystems

For devices such as chip-scale atomic clocks (CSACs) and capacitance diaphragm gauges (CDGs) that require compact vacuum environments at sub-µTorr or even nTorr vacuum levels, the stability of the vacuum is generally of great importance. Miniaturized pumps and gauges can play critical roles in actively maintaining and monitoring chip-scale vacuum environments. Toward this end, this thesis describes two types of elements: (i) miniaturized radio frequency (RF) electron traps for magnet-less ion pumps, and (ii) miniaturized cold cathode gauges to measure vacuum levels. In traditional ion pumps, electrons are confined by crossed electric and magnetic fields in a Penning electron trap in order to extend electron lifetime and promote ionizing electron-gas collisions. However, CSACs are sensitive to magnetic fields. This thesis describes a magnet-less RF electron trap to replace the Penning electron trap for CSAC applications. The RF electron trap was investigated in two generations. The first-generation formed a 0.7 cm3 electron active volume. An RF signal of various power levels and at 143.6 MHz was applied across two RF electrodes spaced 0.7 cm apart to trap electrons that were supplied by an electron gun. It was shown experimentally that the steady state electrode potentials (SSEPs) on electrodes near the trap became more negative after applying certain RF power levels, which indicated higher electron density within the trap. The measured trends aligned well with the modeled trends. The electron density within the trap was estimated to be 3 x 105 cm-3, which was ~1000x the electron density in the electron beam as it exited the electron gun. The second-generation RF electron trap was refined in structure to have 10x finer perforated RF electrodes, a higher trap-to-device volume ratio, simplified electrode composition and RF characteristics, and a tunable operating frequency. The experimental results showed that the electron density was 2.24 x 106 cm-3 in the center of the RF electron trap when the trap was operated at 96.9 MHz with a transmitted RF power of 0.273 W. Both RF electron traps represent successful demonstrations of compact new structures for trapping electrons without using a magnetic field. Miniaturized vacuum gauges allow monitoring of pressure levels in compact systems without introducing significant performance-degrading dead volume. This thesis describes new designs for miniature cold cathode gauges (CCGs). Seven preliminary CCG designs with an internal volume of less than 1 cm3 were developed. Four of these preliminary CCG designs were shown via analysis to be capable of spiraling electrons with a direct current (DC) operating voltage lower than 1000 V. Four CCG designs were further refined to analytically demonstrate better electron spiraling capability while also fulfilling manufacturability requirements. A magnetron design (Design M.S) was fabricated with three-dimensional (3D) printing techniques for performance characterization. The Design M.S could start at a pressure as low as 10.5 µTorr when the power supply VS to the cathode was biased at –750 V, and the gauge current was repeatable from 10-3 Torr to 10-5 Torr at various VS from –750 V to –3000 V. The estimated average magnetic flux density was 0.2 T in Design M.S. The miniaturized CCGs are at least 10x smaller than commercially available CCGs, e.g., the MKS Series 903 inverted magnetron transducer, which has an internal volume of 15 cm3.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/140796/1/kevindsy_1.pd

Energy Measurements of High Performance Computing Systems: From Instrumentation to Analysis

Energy efficiency is a major criterion for computing in general and High Performance Computing in particular. When optimizing for energy efficiency, it is essential to measure the underlying metric: energy consumption. To fully leverage energy measurements, their quality needs to be well-understood. To that end, this thesis provides a rigorous evaluation of various energy measurement techniques. I demonstrate how the deliberate selection of instrumentation points, sensors, and analog processing schemes can enhance the temporal and spatial resolution while preserving a well-known accuracy. Further, I evaluate a scalable energy measurement solution for production HPC systems and address its shortcomings. Such high-resolution and large-scale measurements present challenges regarding the management of large volumes of generated metric data. I address these challenges with a scalable infrastructure for collecting, storing, and analyzing metric data. With this infrastructure, I also introduce a novel persistent storage scheme for metric time series data, which allows efficient queries for aggregate timelines. To ensure that it satisfies the demanding requirements for scalable power measurements, I conduct an extensive performance evaluation and describe a productive deployment of the infrastructure. Finally, I describe different approaches and practical examples of analyses based on energy measurement data. In particular, I focus on the combination of energy measurements and application performance traces. However, interweaving fine-grained power recordings and application events requires accurately synchronized timestamps on both sides. To overcome this obstacle, I develop a resilient and automated technique for time synchronization, which utilizes crosscorrelation of a specifically influenced power measurement signal. Ultimately, this careful combination of sophisticated energy measurements and application performance traces yields a detailed insight into application and system energy efficiency at full-scale HPC systems and down to millisecond-range regions.:1 Introduction 2 Background and Related Work 2.1 Basic Concepts of Energy Measurements 2.1.1 Basics of Metrology 2.1.2 Measuring Voltage, Current, and Power 2.1.3 Measurement Signal Conditioning and Analog-to-Digital Conversion 2.2 Power Measurements for Computing Systems 2.2.1 Measuring Compute Nodes using External Power Meters 2.2.2 Custom Solutions for Measuring Compute Node Power 2.2.3 Measurement Solutions of System Integrators 2.2.4 CPU Energy Counters 2.2.5 Using Models to Determine Energy Consumption 2.3 Processing of Power Measurement Data 2.3.1 Time Series Databases 2.3.2 Data Center Monitoring Systems 2.4 Influences on the Energy Consumption of Computing Systems 2.4.1 Processor Power Consumption Breakdown 2.4.2 Energy-Efficient Hardware Configuration 2.5 HPC Performance and Energy Analysis 2.5.1 Performance Analysis Techniques 2.5.2 HPC Performance Analysis Tools 2.5.3 Combining Application and Power Measurements 2.6 Conclusion 3 Evaluating and Improving Energy Measurements 3.1 Description of the Systems Under Test 3.2 Instrumentation Points and Measurement Sensors 3.2.1 Analog Measurement at Voltage Regulators 3.2.2 Instrumentation with Hall Effect Transducers 3.2.3 Modular Instrumentation of DC Consumers 3.2.4 Optimal Wiring for Shunt-Based Measurements 3.2.5 Node-Level Instrumentation for HPC Systems 3.3 Analog Signal Conditioning and Analog-to-Digital Conversion 3.3.1 Signal Amplification 3.3.2 Analog Filtering and Analog-To-Digital Conversion 3.3.3 Integrated Solutions for High-Resolution Measurement 3.4 Accuracy Evaluation and Calibration 3.4.1 Synthetic Workloads for Evaluating Power Measurements 3.4.2 Improving and Evaluating the Accuracy of a Single-Node Measuring System 3.4.3 Absolute Accuracy Evaluation of a Many-Node Measuring System 3.5 Evaluating Temporal Granularity and Energy Correctness 3.5.1 Measurement Signal Bandwidth at Different Instrumentation Points 3.5.2 Retaining Energy Correctness During Digital Processing 3.6 Evaluating CPU Energy Counters 3.6.1 Energy Readouts with RAPL 3.6.2 Methodology 3.6.3 RAPL on Intel Sandy Bridge-EP 3.6.4 RAPL on Intel Haswell-EP and Skylake-SP 3.7 Conclusion 4 A Scalable Infrastructure for Processing Power Measurement Data 4.1 Requirements for Power Measurement Data Processing 4.2 Concepts and Implementation of Measurement Data Management 4.2.1 Message-Based Communication between Agents 4.2.2 Protocols 4.2.3 Application Programming Interfaces 4.2.4 Efficient Metric Time Series Storage and Retrieval 4.2.5 Hierarchical Timeline Aggregation 4.3 Performance Evaluation 4.3.1 Benchmark Hardware Specifications 4.3.2 Throughput in Symmetric Configuration with Replication 4.3.3 Throughput with Many Data Sources and Single Consumers 4.3.4 Temporary Storage in Message Queues 4.3.5 Persistent Metric Time Series Request Performance 4.3.6 Performance Comparison with Contemporary Time Series Storage Solutions 4.3.7 Practical Usage of MetricQ 4.4 Conclusion 5 Energy Efficiency Analysis 5.1 General Energy Efficiency Analysis Scenarios 5.1.1 Live Visualization of Power Measurements 5.1.2 Visualization of Long-Term Measurements 5.1.3 Integration in Application Performance Traces 5.1.4 Graphical Analysis of Application Power Traces 5.2 Correlating Power Measurements with Application Events 5.2.1 Challenges for Time Synchronization of Power Measurements 5.2.2 Reliable Automatic Time Synchronization with Correlation Sequences 5.2.3 Creating a Correlation Signal on a Power Measurement Channel 5.2.4 Processing the Correlation Signal and Measured Power Values 5.2.5 Common Oversampling of the Correlation Signals at Different Rates 5.2.6 Evaluation of Correlation and Time Synchronization 5.3 Use Cases for Application Power Traces 5.3.1 Analyzing Complex Power Anomalies 5.3.2 Quantifying C-State Transitions 5.3.3 Measuring the Dynamic Power Consumption of HPC Applications 5.4 Conclusion 6 Summary and Outloo

On the spectrometry of laser-accelerated particle bunches and laser-driven proton radiography

The increased availability of high-power laser systems operating with relatively high repetition rates (∼ 1 Hz), such as installed in the upcoming Centre for Advanced Laser Applications (CALA), are pushing laser-driven ion acceleration towards applications beyond fundamental research. With energies of laser-accelerated protons approaching 100 MeV, great interest in the community is devoted to biomedical applications like small-animal irradiation and imaging of biological samples. Such laser-accelerated ion bunches exhibit unique properties as compared to conventionally accelerated particles from electrostatic or radio-frequency driven accelerators. Among these characteristics are high beam intensities (∼ 10^9 protons/ns), a broad energy distribution (∼ 100%) and a strong electromagnetic pulse generated in the laser-plasma interaction. Due to these peculiar properties, conventional beam monitoring devices as installed e.g. in clinical ion beam facilities are not suitable for the characterization of laser-accelerated ion bunches and no system is available to date allowing for online beam monitoring simultaneous to an application. Within the framework of this thesis, two approaches for characterization of laser-accelerated proton bunches in terms of energy spectrum have been investigated and prototype systems have been developed and tested. The first setup is based on the time-of-flight (TOF) technique. The continuous energy distribution is deconvolved from the TOF signal current measured by a novel thin silicon detector which is exposed to temporally divergent polyenergetic proton bunches, taking into account the finite response function of the detector and the associated readout electronics. Measurements were performed in the energy range up to 20 MeV using nanosecond-short and passively energy-modulated proton bunches from a Tandem accelerator, as well as using laser-accelerated proton bunches obtained in experiments at the Laboratory for Extreme Photonics. A comparison of the reconstructed energy spectra to Monte Carlo simulations and measurements using a magnetic spectrometer has shown promising agreement. In the studied energy range and for the tested TOF distances, the reconstructed particle number and the mean reconstructed energy agreed with expectations within 12% and 2%, respectively. In the second investigated setup, the sensor chip of a hybrid pixel detector Timepix was irradiated edge-on with protons in the energy interval between 17 and 20 MeV. Spatial information along one axis perpendicular to the proton beam direction was obtained due to the pixelation of the detector. Although this spectrometric setup is only suitable for low proton fluences (< 7 × 10 3 protons/cm 2 ) per acquisition frame, which is far below typically obtained fluences from laser-ion acceleration experiments, the developed spectrum reconstruction method could be applied to other detector types providing a higher saturation limit than the used Timepix detector. As this thesis is dedicated to biomedical applications using laser-accelerated proton bunches, a feasibility study was performed to assess the applicability of laser-driven proton radiography of millimeter to centimeter sized objects using pixelated semiconductor detectors and polyenergetic proton bunches in the energy ranges up to 20 MeV and up to 100 MeV. The study was based on Monte Carlo simulations and was supported by a proof of principle experiment with an energy-modulated proton beam from a conventional Tandem accelerator. Sub-mm spatial resolution and density resolution below 3% were found for all objects investigated within this study and the optimized geometric distances. Motivated by the promising results obtained within this thesis, the TOF spectrometer will be implemented as diagnostic device in the laser-ion acceleration setup at CALA in the near future. Moreover, a radiographic imaging setup using laser-accelerated proton bunches and pixelated silicon detector, based on the results obtained within this thesis, is foreseen.Die vermehrte Verfügbarkeit von Hochleistungslasersystemen mit relativ hohen Pulswiederholungsraten (∼ 1 Hz), wie beispielsweise im Centre for Advanced Laser Applications (CALA), öffnen neue Wege für Anwendungen von Laser-Ionen-Beschleunigung, die über die Grundlagenforschung hinausreichen. Da sich die erzielten Energien von laser-beschleunigten Protonen den 100 MeV annähern, steigt das Interesse an biomedizinischen Anwendungen wie beispielsweise Kleintierbestrahlungen und Bildgebung von biologischen Proben. Die Eigenschaften solcher laser-beschleunigter Ionenpulse sind einzigartig verglichen mit konventionell beschleunigten Teilchen von elektrostatischen oder von Beschleunigern basierend auf elektromagnetischen Wechselfeldern. Zu den Merkmalen zählen die hohen Intensitäten (∼ 10^9 Protonen/ns), ein breites Energiespektrum (∼ 100%) und der starke elektromagnetische Puls, der in der Laser-Plasma-Interaktion erzeugt wird. Aufgrund dieser besonderen Eigenschaften sind herkömmliche Strahlüberwachungssysteme, wie beispielsweise in klinischen Ionenstrahleinrichtungen eingesetzt, nicht geeignet. Bisher ist kein System verfügbar, welches eine Echtzeitstrahlüberwachung parallel zu einer Anwendung erlaubt. Im Zuge dieser Arbeit wurden zwei Ansätze zur Charakterisierung laser-beschleunigter Protonenpulse hinsichtlich ihres Energiespektrums untersucht. Prototypen wurden entwickelt und getestet. Der erste Ansatz basiert auf der Flugzeitmessung (time-of-flight - TOF). Die kontinuierliche Energieverteilung wird aus dem gemessenen TOF-Signal herausgefaltet. Dieses wird mit Hilfe eines neuartigen dünnen Siliziumdetektors aufgezeichnet, der dem zeitlich auseinanderlaufenden polyenergetischen Protonenpuls exponiert ist. Die Ansprechfunktion des Detektors und der zugehörigen Ausleseelektronik wird hierbei berücksichtigt. Messungen wurden im Energiebereich bis 20 MeV mit nanosekunden-kurzen und passiv Energie-modulierten Protonenpulsen eines Tandem-Beschleunigers, sowie mit laser-beschleunigten Protonenpulsen am Laboratory for Extreme Photonics, durchgeführt. Vielversprechende Übereinstimmungen wurden beim Vergleich der rekonstruierten Energieverteilung zu Monte-Carlo Simulationen und zu Messungen mit Hilfe eines Magnetspektrometers gefunden. Für den getesteten Energiebereich und TOF-Distanzen waren die Abweichungen zwischen Rekonstruktion und Erwartungen bei Teilchenzahl und mittlerer Energie kleiner als 12%, beziehungsweise 2%. Im zweiten untersuchten Aufbau wurde die Sensorchipkante des hybriden Pixeldetektors Timepix mit Protonen im Energieintervall zwischen 17 und 20 MeV bestrahlt. Räumliche Information entlang einer Achse senkrecht zur Strahlrichtung wurde aufgrund der Pixelierung des Detektors erhalten. Dieser spektrometrische Aufbau ist nur für niedrige Protonenfluenzen (< 7 × 10 3 Protonen/cm 2 ) pro Aufnahmebild, welche weit unter typischen Fluenzen in Laser-Ionen-Beschleunigung liegt, geeignet. Dennoch kann die in dieser Arbeit entwickelte Rekonstruktionsmethode für andere Detektortypen, mit höherer Sättigungsgrenze als der Timepix-Detektor, angewandt werden. Da diese Dissertation das Ziel einer biomedizinische Anwendung von laser-beschleunigten Protonenpulsen verfolgt, wurde eine Studie durchgeführt um die Machbarkeit von laserbeschleunigter Protonenradiographie von Millimeter- bis Zentimeter-großen Objekten und pixelierten Halbleiterdetektoren zu eruieren. Der Energiebereich der polyenergetischen Protonenpulse war hierbei bis 20 MeV und bis 100 MeV. Die Studie basiert auf Monte-Carlo Simulationen und wurde durch ein Proof-of-Principle Experiment mit einem Energiemodulierten Protonenstrahl von einem Tandembeschleuniger unterstützt. Die gefundene räumliche Auflösung und die Dichteauflösung war im sub-Millimeterbereich, bzw. besser als 3% für alle in dieser Studie getesteten Objekte und für die optimierten geometrischen Abstände. Aufgrund der vielversprechenden Ergebnisse, die im Zuge dieser Arbeit gewonnen wurden, wird das Flugzeitspektrometer als diagnostisches System für die Laser-Ionen-Beschleunigung an CALA in naher Zukunft eingesetzt. Desweiteren ist ein Aufbau zur Bildgebung mittels laser-beschleunigter Protonen und einem pixelierten Siliziumdetektor, basierend auf den in dieser Arbeit erzielten Ergebnisse, vorgesehen