By Hong Shen (auth.), Anu G. Bourgeois, S. Q. Zheng (eds.)
This publication constitutes the refereed lawsuits of the eighth overseas 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 geared up in topical sections on scheduling and cargo balancing, interconnection networks, parallel algorithms, allotted structures, parallelization instruments, grid computing, and software program systems.
Read or Download Algorithms and Architectures for Parallel Processing: 8th International Conference, ICA3PP 2008, Cyprus, June 9-11, 2008 Proceedings PDF
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Extra info for Algorithms and Architectures for Parallel Processing: 8th International Conference, ICA3PP 2008, Cyprus, June 9-11, 2008 Proceedings
The simulation results show that our algorithm often succeed in ﬁnding best schedule that ﬁt more to the real applications from those schedules which are considered the same in other algorithms that use constant computation costs and communication costs. Example 1. In the ﬁrst example, we assume that processors in target system are homogeneous, and all of the computation costs and communication costs are normally distributed variables, which may ﬁt more than other distributions to real applications.
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. Yang et al. be executed before nj . If there are no precedence relations between two nodes, however, they can be executed in any order in that processor.
1, will be used as an example later. 20 J. Yang et al. n1 Z(n1) e12 n2 e17 Z(n2) e26 e15 e14 e13 n3 n4 n5 Z(n3) Z(n4) Z(n5) e27 e38 e48 n6 n7 n8 Z(n6) Z(n7) Z(n8) e69 e79 e89 n9 Z(n9) Fig. 1. Example of a DAG Table 1. 2 21 Computing Top Levels The top level  (t-level ) of a node ni is the length of a longest path (there can be more than one longest path) from an entry node to ni excluding ni . An algorithm for computing the t-levels is shown below. Because computation costs and communication costs are supposed to be stochastic variables in this paper, notations in the algorithm, like ω(ni ) and c(ni , nj ), denote samples of computation costs and communication costs.