0000000000403196
AUTHOR
Radu Chis
Forecasting Electricity Consumption and Production in Smart Homes through Statistical Methods
Abstract Over the last years, a steady increase in both domestic electricity consumption and in the adoption of personal clean energy production systems has been observed worldwide. By analyzing energy consumption and production on photovoltaic panels mounted in a house, this work focuses on finding patterns in electrical energy consumption and devising a predictive model. Our goal is to find an accurate method to predict electrical energy consumption and production. Being able to anticipate how consumers will use energy in the near future, homeowners, companies and governments may optimize their behavior and the import and export of electricity. We evaluated the ARIMA and TBATS statistical…
Multi-objective DSE algorithms' evaluations on processor optimization
Very complex micro-architectures, like complex superscalar/SMT or multicore systems, have lots of configurations. Exploring this huge design space and trying to optimize multiple objectives, like performance, power consumption and hardware complexity is a real challenge. In this paper, using the multi-objective design space exploration tool FADSE, we tried to optimize the hardware parameters of the complex superscalar Grid ALU Processor. We compared how different heuristic algorithms handle the DSE optimization. Three of these algorithms are taken from the jMetal library (NSGAII, SPEA2 and SMPSO) while the other two, CNSGAII and MOHC were implemented by us. We show that in this huge design …
Enhancing the Sniper Simulator with Thermal Measurement
This paper presents the enhancement of the Sniper multicore / manycore simulator with thermal measurement possibilities using the HotSpot simulator. We present a plugin that interacts with Sniper to retrieve simulation data (integration areas and power consumptions) and calls HotSpot to compute the corresponding thermal results. The plugin also builds a two dimensional floorplan for the simulated microarchitecture. Furthermore we plan to integrate the simulation methodology presented here into an automatic design space exploration process using the multi-objective optimization tool called FADSE. Keywords—multicore; simulator; power consumption; thermal; HotSpot; Sniper
Improving Computing Systems Automatic Multiobjective Optimization Through Meta-Optimization
This paper presents the extension of framework for automatic design space exploration (FADSE) tool using a meta-optimization approach, which is used to improve the performance of design space exploration algorithms, by driving two different multiobjective meta-heuristics concurrently. More precisely, we selected two genetic multiobjective algorithms: 1) non-dominated sorting genetic algorithm-II and 2) strength Pareto evolutionary algorithm 2, that work together in order to improve both the solutions’ quality and the convergence speed. With the proposed improvements, we ran FADSE in order to optimize the hardware parameters’ values of the grid ALU processor (GAP) micro-architecture from a b…