14 research outputs found
Componentes de produção de pinhão manso irrigado com água de diferentes condutividades elétrica e doses de fósforo
Energetic sustainability of three arabica coffee growing systems used by family farming units in Espírito Santo state
Metodologia para produção de Metarhizium anisopliae (METSCH.) sorokin em cultivo submerso: esporulação da biomassa, efeito da concentração de açúcar e custo do inoculant
Passive Q-switching and mode-locking for the generation of nanosecond to femtosecond pulses
Performance Evaluation of Work Stealing for Streaming Applications
International audienceThis paper studies the performance of parallel stream computations on a multiprocessor architecture using a work-stealing strategy. Incoming tasks are split in a number of jobs allocated to the processors and whenever a processor becomes idle, it steals a fraction (typically half) of the jobs from a busy processor. We propose a new model for the performance analysis of such parallel stream computations. This model takes into account both the algorithmic behavior of work-stealing as well as the hardware constraints of the architecture (synchronizations and bus contentions). Then, we show that this model can be solved using a recursive formula. We further show that this recursive analytical approach is more efficient than the classic global balance technique. However, our method remains computationally impractical when tasks split in many jobs or when many processors are considered. Therefore, bounds are proposed to efficiently solve very large models in an approximate manner. Experimental results show that these bounds are tight and robust so that they immediately find applications in optimization studies. An example is provided for the optimization of energy consumption with performance constraints. In addition, our framework is flexible and we show how it adapts to deal with several stealing strategies