Download Algorithms and Architectures for Parallel Processing: 8th by Hong Shen (auth.), Anu G. Bourgeois, S. Q. Zheng (eds.) PDF

By Hong Shen (auth.), Anu G. Bourgeois, S. Q. Zheng (eds.)

This publication constitutes the refereed court cases of the eighth foreign convention on Algorithms and Architectures for Parallel Processing, ICA3PP 2008, held in Agia Napa, Cyprus, in June 2008.

The 31 revised complete papers offered including 1 keynote speak and 1 educational have been rigorously reviewed and chosen from 88 submissions. The papers are equipped in topical sections on scheduling and cargo balancing, interconnection networks, parallel algorithms, dispensed structures, parallelization instruments, grid computing, and software program systems.

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Extra info for Algorithms and Architectures for Parallel Processing: 8th International Conference, ICA3PP 2008, Cyprus, June 9-11, 2008 Proceedings

Example text

Morana Step 1 and Step 2: trails evaluation (construction and selection of solution) and pheromone evaporation Each time a job arrives at the scheduler, it has to decide in which node the job has to be allocated. In our algorithm this decision is taken basing on pheromone trails, following the strategy of the aliened ant. The scheduler assigns a probability value to the underlying resources, basing on the value of the relevant entry in the trails vector. The probability for the ith resource is calculated as: 1− phresi phresT OT (1) where phresi is the value of pheromone trail related to the ith resource and phresT OT is the sum of pheromone trails of all resources.

Endfor . x =x . 2 Stochastic Programming Model For the multiprocessor scheduling problem, we can consider factors such as throughput, makespan, and processor utilization for the objective function. The objective function used for our algorithm is based on makespan, the overall finish-time of a parallel program. The makespan of a schedule is defined as follows: f (ω, c, x , y ) = max F T (ni ) ni ∈V (1) F T (ni ) denotes finishing time of node ni . For a given DAG, the makespan is a function of computation costs ω, communication costs c and the legal schedule (x , y ).

Thus the schedule of all processors is as follows: Processor 1: nxy0 +1 → nxy0 +2 → . . → nxy1 ; Processor 2: nxy1 +1 → nxy1 +2 → . . → nxy2 ; ... Processor p: nxyp−1 +1 → nxyp−1 +2 → . . → nxyp . 1 Generating Legal Schedule For a given random integer decision vectors (x, y), we have to rearrange them to guarantee that the precedence constraints are not violated. For example, if there are precedence relations between two nodes ni and nj , eij ∈ E, and both of them are assigned to the same processor, we should guarantee that ni will 22 J.

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