Abstract. Grid computing is a computing framework to meet the growing computational demands. This paper introduces a novel approach based on Particle Swarm Optimization (PSO) for s...
We present a compiler optimization approach that uses the simulated evolution (SE) paradigm to enhance the finish time of heuristically scheduled computations with communication t...
Scientific investigations have to deal with rapidly growing amounts of data from simulations and experiments. During data analysis, scientists typically want to extract subsets o...
Alexandru Romosan, Doron Rotem, Arie Shoshani, Der...
This paper presents a new approach for analyzing the performance of grid scheduling algorithms for tasks with dependencies. Finding the optimal procedures for DAG scheduling in Gr...
—Due to the dynamic nature of grid environments, schedule algorithms always need assistance of a long-time-ahead load prediction to make decisions on how to use grid resources ef...