Energy consumption of parallel algorithms for solving linear systems on HPC architecture

Modern High-Performance Computing HPC systems are gradually increasing in size and complexity due to the correspondent demand of larger simulations requiring more complicated tasks and higher accuracy. However, as side effects of the Dennard’s scaling approaching its ultimate power limit, the efficiency of software plays also an important role in increasing the overall performance of a computation. Tools to measure application performance in these increasingly complex environments provide insights into the intricate ways in which software and hardware interact. The monitoring of the power consumption in order to save energy is possible through processors interfaces like Intel Running Average Power Limit RAPL. Given the low level of these interfaces, they are often paired with an application-level tool like Performance Application Programming Interface PAPI. Since several problems in many heterogeneous fields can be represented as a complex linear system, an optimized and scalable linear system solver algorithm can decrease significantly the time spent to compute its resolution. One of the most widely used algorithms deployed for the resolution of large simulation is the Gaussian Elimination, which has its most popular implementation for HPC systems in the Scalable Linear Algebra PACKage ScaLAPACK library. However, another relevant algorithm, which is increasing in popularity in the academic field, is the Inhibition Method. This thesis compares the energy consumption of the Inhibition Method and Gaussian Elimination from ScaLAPACK to profile their execution during the resolution of linear systems above the HPC architecture offered by CINECA. Moreover, it also collates the energy and power values for different ranks, nodes, and sockets configurations. The monitoring tools employed to track the energy consumption of these algorithms are PAPI and RAPL, that will be integrated with the parallel execution of the algorithms managed with the Message Passing Interface MPI.

Development and testing of a virtual energy meter using the Labview Environment

The quantity of electric energy utilized by a home, a business, or an electrically powered device is measured by an electricity meter, also known as an electric meter, electrical meter, or energy meter. Electric meters located at customers' locations are used by electric providers for billing. They are usually calibrated in billing units, with the kilowatt hour being the most popular (kWh). Typically, they are read once each billing cycle. When energy savings are sought during specific times, some meters may monitor demand, or the highest amount of electricity used during a specific time. Additionally, some meters feature relays for load shedding in response to responses during periods of peak load. The amount of electrical energy consumed by users is measured by a Watt-hour meter, also known as an energy meter. To charge the electricity usage by loads like lights, fans, and other appliances, utilities put these gadgets everywhere, including in households, businesses, and organizations. Watts are a fundamental power unit. A kilowatt is equal to one thousand watts. One kilowatt is regarded as one unit of energy used if used for one hour. These meters calculate the product of the instantaneous voltage and current readings and provide instantaneous power. This power is distributed over a period and is used during that time. Depending on the supply used by home or commercial installations, these may be single or three phase meters. These can be linked directly between line and load for minor service measurements, such as home consumers. However, step-down current transformers must be installed for greater loads to handle their higher current demands.

Evaluation of the power production performance of the wavepiston, wave energy converter

In the early 1970 the community has started to realize that have as a main principle the industry one, with the oblivion of the people and health conditions and of the world in general, it could not be a guideline principle. The sea, as an energy source, has the characteristic of offering different types of exploitation, in this project the focus is on the wave energy. Over the last 15 years the Countries interested in the renewable energies grew. Therefore many devices have came out, first in the world of research, then in the commercial one; these converters are able to achieve an energy transformation into electrical energy. The purpose of this work is to analyze the efficiency of a new wave energy converter, called WavePiston, with the aim of determine the feasibility of its actual application in different wave conditions: from the energy sea state of the North Sea, to the more quiet of the Mediterranean Sea. The evaluation of the WavePiston is based on the experimental investigation conducted at the University of Aalborg, in Denmark; and on a numerical modelling of the device in question, to ascertain its efficiency regardless the laboratory results. The numerical model is able to predict the laboratory condition, but it is not yet a model which can be used for any installation, in fact no mooring or economical aspect are included yet. È dai primi anni del 1970 che si è iniziato a capire che il solo principio dell’industria con l’incuranza delle condizioni salutari delle persone e del mondo in generale non poteva essere un principio guida. Il mare, come fonte energetica, ha la caratteristica di offrire diverse tipologie di sfruttamento, in questo progetto è stata analizzata l’energia da onda. Negli ultimi 15 anni sono stati sempre più in aumento i Paesi interessati in questo ambito e di conseguenza, si sono affacciati, prima nel mondo della ricerca, poi in quello commerciale, sempre più dispositivi atti a realizzare questa trasformazione energetica. Di tali convertitori di energia ondosa ne esistono diverse classificazioni. Scopo di tale lavoro è analizzare l’efficienza di un nuovo convertitore di energia ondosa, chiamato WavePiston, al fine si stabilire la fattibilità di una sua reale applicazione in diverse condizioni ondose: dalle più energetiche del Mare del Nord, alle più quiete del Mar Mediterraneo. La valutazione sul WavePiston è basata sullo studio sperimentale condotto nell’Università di Aalborg, in Danimarca; e su di una modellazione numerica del dispositivo stesso, al fine di conoscerne l’efficienza a prescindere dalla possibilità di avere risultati di laboratorio. Il modello numerico è in grado di predirre le condizioni di laboratorio, ma non considera ancora elementi come gli ancoraggi o valutazione dei costi.

Progetto e valutazione di una piattaforma sperimentale di Internet of Energy per veicoli elettrici

This dissertation deals with the development of a project concerning a demonstration in the scope of the Supply Chain 6 of the Internet of Energy (IoE) project: the Remote Monitoring Emulator, which bears my personal contribution in several sections. IoE is a project of international relevance, that means to establish an interoperability standard as regards the electric power production and utilization infrastructure, using Smart Space platforms. The future perspectives of IoE have to do with a platform for electrical power trade-of, the Smart Grid, whose energy is produced by decentralized renewable sources and whose services are exploited primarily according to the Internet of Things philosophy. The main consumers of this kind of smart technology will be Smart Houses (that is to say, buildings controlled by an autonomous system for electrical energy management that is interoperable with the Smart Grid) and Electric Mobility, that is a smart and automated management regarding movement and, overall, recharging of electrical vehicles. It is precisely in the latter case study that the project Remote Monitoring Emulator takes place. It consists in the development of a simulated platform for the management of an electrical vehicle recharging in a city. My personal contribution to this project lies in development and modeling of the simulation platform, of its counterpart in a mobile application and implementation of a city service prototype. This platform shall, ultimately, make up a demonstrator system exploiting the same device which a real user, inside his vehicle, would use. The main requirements that this platform shall satisfy will be interoperability, expandability and relevance to standards, as it needs to communicate with other development groups and to effectively respond to internal changes that can affect IoE.

Hydraulic evaluation of the gyro electric wave energy converter

Motivation Thanks for a scholarship offered by ALma Mater Studiorum I could stay in Denmark for six months during which I could do physical tests on the device Gyro PTO at the Departmet of Civil Engineering of Aalborg University. Aim The goal of my thesis is an hydraulic evaluation of the device: Gyro PTO, a gyroscopic device for conversion of mechanical energy in ocean surface waves to electrical energy. The principle of the system is the application of the gyroscopic moment of flywheels equipped on a swing float excited by waves. The laboratory activities were carried out by: Morten Kramer, Jan Olsen, Irene Guaraldi, Morten Thøtt, Nikolaj Holk. The main purpose of the tests was to investigate the power absorption performance in irregular waves, but testing also included performance measures in regular waves and simple tests to get knowledge about characteristics of the device, which could facilitate the possibility of performing numerical simulations and optimizations. Methodology To generate the waves and measure the performance of the device a workstation was created in the laboratory. The workstation consist of four computers in each of wich there was a different program. Programs have been used : Awasys6, LabView, Wave lab, Motive optitrack, Matlab, Autocad Main Results Thanks to the obtained data with the tank testing was possible to make the process of wave analisys. We obtained significant wave height and period through a script Matlab and then the values of power produced, and energy efficiency of the device for two types of waves: regular and irregular. We also got results as: physical size, weight, inertia moments, hydrostatics, eigen periods, mooring stiffness, friction, hydrodynamic coefficients etc. We obtained significant parameters related to the prototype in the laboratory after which we scale up the results obtained for two future applications: one in Nissun Brending and in the North Sea. Conclusions The main conclusion on the testing is that more focus should be put into ensuring a stable and positive power output in a variety of wave conditions. In the irregular waves the power production was negative and therefore it does not make sense to scale up the results directly. The average measured capture width in the regular waves was 0.21 m. As the device width is 0.63 m this corresponds to a capture width ratio of: 0.21/0.63 * 100 = 33 %. Let’s assume that it is possible to get the device to produce as well in irregular waves under any wave conditions, and lets further assume that the yearly absorbed energy can be converted into electricity at a PTO-efficiency of 90 %. Under all those assumptions the results in table are found, i.e. a Nissum Bredning would produce 0.87 MWh/year and a North Sea device 85 MWh/year.

Energy harvesting from piezoelectric devices embedded in a 3D printed wing

This thesis work has been carried out at Clarkson University in Potsdam NY, USA and involved the design of a low elongation wing, consisting of parts made by polylactide (PLA) using the fused deposition model (FDM) technology of Rapid Prototyping, then assembled together in a thin aluminum spar. The aim of the research is to evaluate the feasibility of collecting electrical energy by converting mechanical energy from the vibration of the wing flutter. With this aim piezoelectric stripes were glued in the inner part of the wing, as well as on the aluminum spar, as monomorphic configuration. During the phases of the project, particular attention was given to the geometry and the materials used, in order to trigger the flutter for low flow velocity. The CAD software SolidWorks® was used for the design of the wing and then the drawings were sent to the Clarkson machine shop in order to to produce the parts required by the wing assembly. FEM simulations were performed, using software MSC NASTRAN/PATRAN®, to evaluate the stiffness of the whole wing as well as the natural vibration modes of the structure. These data, in a first approximation, were used to predict the flutter speed. Finally, experimental tests in the Clarkson wind tunnel facility were carried out in order to validate the results obtained from FEM analysis. The power collected by the piezoelectrics under flutter condition was addressed by tuning the resistors downstream the electronic circuit of the piezoelectrics.

Motor Unit Spike Trains Recontruction from sEMG Signals for Gesture Classification on a Low-Power Processing Platform

Hand gesture recognition based on surface electromyography (sEMG) signals is a promising approach for the development of intuitive human-machine interfaces (HMIs) in domains such as robotics and prosthetics. The sEMG signal arises from the muscles' electrical activity, and can thus be used to recognize hand gestures. The decoding from sEMG signals to actual control signals is non-trivial; typically, control systems map sEMG patterns into a set of gestures using machine learning, failing to incorporate any physiological insight. This master thesis aims at developing a bio-inspired hand gesture recognition system based on neuromuscular spike extraction rather than on simple pattern recognition. The system relies on a decomposition algorithm based on independent component analysis (ICA) that decomposes the sEMG signal into its constituent motor unit spike trains, which are then forwarded to a machine learning classifier. Since ICA does not guarantee a consistent motor unit ordering across different sessions, 3 approaches are proposed: 2 ordering criteria based on firing rate and negative entropy, and a re-calibration approach that allows the decomposition model to retain information about previous sessions. Using a multilayer perceptron (MLP), the latter approach results in an accuracy up to 99.4% in a 1-subject, 1-degree of freedom scenario. Afterwards, the decomposition and classification pipeline for inference is parallelized and profiled on the PULP platform, achieving a latency < 50 ms and an energy consumption < 1 mJ. Both the classification models tested (a support vector machine and a lightweight MLP) yielded an accuracy > 92% in a 1-subject, 5-classes (4 gestures and rest) scenario. These results prove that the proposed system is suitable for real-time execution on embedded platforms and also capable of matching the accuracy of state-of-the-art approaches, while also giving some physiological insight on the neuromuscular spikes underlying the sEMG.