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Item Open Access Dataset associated with "Device Characterization on Energy Design and Scoping Tool for DC Distribution Systems and a Study on Harmonics in AC/DC Converters in Low Voltage Distribution" and "Efficiency of AC vs. DC Distribution Systems in Commercial Buildings”(Colorado State University. Libraries, 2020) Santos, ArthurDC appliances have resurged with the evolution of power electronics and their massive application in Miscellaneous Electric Loads. The increase of DC distributed generation and battery storage also helped boosting the scientific community's attention to this other alternative. This work collects consumption data from appliances and converters connected to an AC distribution. The appliances that are focused in this study are also called Miscellaneous Electric Loads (MELs), which comprise all electronic loads in a building that are not related to lighting, heating, and air conditioning. Harmonics for these devices are analyzed, as this is part of a relevant project funded by the Department of Energy of the United States: the Energy Design and Scoping Tool for DC Distribution Systems. This work also presents results from another study, still within the scope of the same project, which aims to collect power consumption over a period of approximately two months of appliances commonly found in an office environment (laptop, screens, desktops, phone chargers and network devices). The data provided by this experiment will give a real estimate of these appliances' AC/DC converters operating range regarding their rated power. This will allow a more complete analysis to be carried out regarding the emission of harmonics in the power system and also a comparison between harmonic cancellation that is more likely to be occurring in low voltage distribution systems compared to the total cancellation potential.Item Open Access Dataset associated with "Polyhedral optimizations of RNA-RNA interaction computations"(Colorado State University. Libraries, 2017) Varadarajan, SwethaStudying RNA-RNA interaction has led to major successes in the treatment of some cancers, including colon, breast and pancreatic cancer by suppressing the gene expression involved in the development of these diseases. The problem with such programs is that they are computationally and memory intensive: O(N4) space and O(N6) time complexity. Moreover, the entire applicationis complicated and involves many mutually recursive data variables. We address the problem of speeding up a surrogate kernel (named OSPSQ) that captures the main dependence pattern foundin two widely used RNA-RNA interaction applications- IRIS and piRNA. The structure of the OSPSQ kernel perfectly fits the constraints of the polyhedral model, a well-developed technology for optimizing codes that belong to many specialized domains. However, the current state-of-the-art automatic polyhedral tools do not significantly improve the performance of the baseline implementation of OSPSQ. With simple techniques like loop permutation and skewing, we achieve an average of 17x sequential and 31x parallel speedup on a standard modern multi-core platform (Intel Broadwell, E5-1650v4). This performance represents 75% and 88% of attainable single-core and multi-core L1 bandwidth. For further performance improvement, we describe how to tile all six dimensions and also formulate the associated memory trade-off. In the future, we plan to implement these tiling strategies, explore the performance of the code for various tile sizes and optimize the whole piRNA application.Item Open Access Toolkits for feature extraction and characterization of network data(Colorado State University. Libraries, 2015-03-29) Bandara, Vidarshana W.