0000000000953816

AUTHOR

Maria Vintan

showing 3 related works from this author

Multi-objective DSE algorithms' evaluations on processor optimization

2013

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 …

Power consumptionComputer scienceHeuristic (computer science)Design space explorationFeature extractionProcess (computing)Feature selectionParallel computingGridDesign spaceAlgorithm2013 IEEE 9th International Conference on Intelligent Computer Communication and Processing (ICCP)
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Ground fault distribution on overhead transmission lines

2006

When a ground fault occurs on an overhead transmission line in a power network with grounded neutral, the fault current returns to the grounded neutral through the tower structures, ground return paths and ground wires. This paper presents an analytical method in order to evaluate the ground fault current distribution in an effectively grounded power network. The effect of soil resistivity, ground resistance of towers and power line configuration, on the magnitude of return currents, has been examined.

Engineeringbusiness.industrySoil resistivityElectrical engineeringLine (electrical engineering)Fault indicatorPower (physics)Electric power transmissionTransmission lineElectronic engineeringGeneral Earth and Planetary SciencesOverhead (computing)businessTowerGeneral Environmental ScienceFacta universitatis - series: Electronics and Energetics
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Unbiased Branches: An Open Problem

2007

The majority of currently available dynamic branch predictors base their prediction accuracy on the previous k branch outcomes. Such predictors sustain high prediction accuracy but they do not consider the impact of unbiased branches, which are difficult-to-predict. In this paper, we evaluate the impact of unbiased branches in terms of prediction accuracy on a range of branch difference predictors using prediction by partial matching, multiple Markov prediction and neural-based prediction. Since our focus is on the impact that unbiased branches have on processor performance, timing issues and hardware costs are out of scope of this investigation. Our simulation results, with the SPEC2000 in…

Mathematical optimizationMarkov chainComputer sciencebusiness.industryOpen problemPrediction by partial matchingBest linear unbiased predictionMachine learningcomputer.software_genreBranch predictorBenchmark (computing)Range (statistics)Artificial intelligenceHardware_CONTROLSTRUCTURESANDMICROPROGRAMMINGbusinesscomputerInteger (computer science)
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