Simulation-based reinforcement learning for real-world autonomous driving

We use reinforcement learning in simulation to obtain a driving system controlling a full-size real-world vehicle. The driving policy takes RGB images from a single camera and their semantic segmentation as input. We use mostly synthetic data, with labelled real-world data appearing only in the training of the segmentation network. Using reinforcement learning in simulation and synthetic data is motivated by lowering costs and engineering effort. In real-world experiments we confirm that we achieved successful sim-to-real policy transfer. Based on the extensive evaluation, we analyze how design decisions about perception, control, and training impact the real-world performance

A job dispatcher for large and heterogeneous HPC systems running modern applications

High-performance Computing (HPC) systems have become essential instruments in our modern society. As they get closer to exascale performance, HPC systems become larger in size and more heterogeneous in their computing resources. With recent advances in AI, HPC systems are also increasingly being used for applications that employ many short jobs with strict timing requirements. HPC job dispatchers need to therefore adopt techniques to go beyond the capabilities of those developed for small or homogeneous systems, or for traditional compute-intensive applications. In this paper, we present a job dispatcher suitable for today's large and heterogeneous systems running modern applications. Unlike its predecessors, our dispatcher solves the entire dispatching problem using Constraint Programming (CP) with a model size independent of the system size. Experimental results based on a simulation study show that our approach can bring about significant performance gains over the existing CP-based dispatchers in a large or heterogeneous system

Long-Term Durability of Rooftop Grid-Connected Solar Photovoltaic Systems

Compared to their initial performance, solar photovoltaic (PV) arrays show long-term performance degradation, resulting in lower like-for-like efficiencies and performance ratios. The long-term durability of polycrystalline silicon (p-Si) solar PV modules in three roof-top grid-connected arrays has been examined. Electrical output, ambient temperature, cell temperature, solar irradiance, solar irradiation, and wind speed data were collected at hourly intervals from 2017 to 2021 from three 50 kWp PV installations in Northern Ireland. The results show the extent to which higher PV temperatures associated with more intense solar radiation decrease efficiency, fill factor and maximum power output for PV arrays in a temperate climate. Long-term durability trends for grid-connected roof-top solar photovoltaic systems can be obscured by diurnal and seasonal changes in environmental conditions. To reduce the influence of variable conditions, performance ratios (PRcorr) were “corrected” using the measured annual average cell temperature (Tcell_avg). Introduction of this temperature-correction reduced the seasonal variation of the performance ratio. Using temperature-corrected performance ratios, long-term (in this case those seen after fiveyears operation) performance degradation trends become evident with high confidence after six months for one PV array and within three years for the two other arrays. If lower statistical confidence in trends is acceptable, long-term degradation rates can be identified within one year of operation for all PV arrays examined. These results have the important implication that relatively short-duration outdoor PV performance monitoring may be reliably used to estimate long-term degradation and/or to calibrate normally-conducted accelerated testing

A High-Performance Design, Implementation, Deployment, and Evaluation of The Slim Fly Network

Novel low-diameter network topologies such as Slim Fly (SF) offer significant cost and power advantages over the established Fat Tree, Clos, or Dragonfly. To spearhead the adoption of low-diameter networks, we design, implement, deploy, and evaluate the first real-world SF installation. We focus on deployment, management, and operational aspects of our test cluster with 200 servers and carefully analyze performance. We demonstrate techniques for simple cabling and cabling validation as well as a novel high-performance routing architecture for InfiniBand-based low-diameter topologies. Our real-world benchmarks show SF's strong performance for many modern workloads such as deep neural network training, graph analytics, or linear algebra kernels. SF outperforms non-blocking Fat Trees in scalability while offering comparable or better performance and lower cost for large network sizes. Our work can facilitate deploying SF while the associated (open-source) routing architecture is fully portable and applicable to accelerate any low-diameter interconnect

PV System Design and Performance

Photovoltaic solar energy technology (PV) has been developing rapidly in the past decades, leading to a multi-billion-dollar global market. It is of paramount importance that PV systems function properly, which requires the generation of expected energy both for small-scale systems that consist of a few solar modules and for very large-scale systems containing millions of modules. This book increases the understanding of the issues relevant to PV system design and correlated performance; moreover, it contains research from scholars across the globe in the fields of data analysis and data mapping for the optimal performance of PV systems, faults analysis, various causes for energy loss, and design and integration issues. The chapters in this book demonstrate the importance of designing and properly monitoring photovoltaic systems in the field in order to ensure continued good performance

Development of a spectral dependent electrical & thermal model for high concentrating photovoltaic (HCPV) receivers

High concentrating photovoltaic (HCPV) systems employ III-V multijunction (MJ) solar cells. Such solar cells are monolithically connected in-series and therefore present a strong dependence on the solar spectrum variations. In addition, the concentrated solar flux contributes to the heat generation within the solar cells and, in combination with the current mismatch between the subcells, can force the device to operate in elevated temperatures. It is important therefore, to investigate the influence of the atmospheric parameters on the electrical performance of HCPV and also to quantify the cooling requirements based on the spectrum changes. In this thesis, a spectral dependent electrical model has been developed to calculate the electrical characteristics and quantify the heat power of a multijunction solar cell. A three-dimensional finite element analysis is also used to predict the solar cell's operating temperature and cooling requirements for a range of ambient temperatures. The combination of these models improves the prediction accuracy of the electrical and thermal behaviour of triple-junction solar cells. The convective heat transfer coefficient between the back-plate and ambient air is quantified based on input spectra. A theoretical investigation is performed to analyse the influence of air mass (AM), aerosol optical depth (AOD) and precipitable water (PW) on the performance of each subcell and whole. It has been shown that the AM and AOD have a negative impact on the spectral and electrical performance of 3J solar cells while the PW has a positive effect, although, to a lesser degree. In order to get a more realistic assessment and also to investigate the effect of heat transfer coefficient on the annual energy yield, the methodology is applied to four US locations using data from a typical meteorological year (TMY3). The integrated modelling procedure is validated experimentally using field measurements from Albuquerque, NM. The importance of the effect of atmospheric parameters on the solar spectrum and hence the performance of HCPV systems is highlighted in this work. The outdoor characterisation provides with useful insight of the influence of spectrum on the performance of a HCPV monomodule and the current CSOC and CSTC ratings are evaluated based on different spectral filtering criteriaESPR