Toward Automatic Data Distribution for Migrating Computations

Pan, Lei; Xie, Jingling; Lai, Ming Kin; Dillencourt, Michael B.; Bic, Lubomir

doi:10.1109/icpp.2007.80

Cited by 5 publications

(6 citation statements)

References 13 publications

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“…To reveal this situation and to change the data exchange scheme within the framework of the approach being considered, the corresponding algorithm should be additionally investigated as is shown in [18]. Other solutions to this problem are proposed in [20,21].…”

Section: Introductionmentioning

confidence: 97%

Parallelization of sequential programs: distribution of arrays among processors and structurization of communications

Adutskevich

Likhoded

Sikorsky³

2012

Cybern Syst Anal

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Section: Introductionmentioning

confidence: 97%

Parallelization of sequential programs: distribution of arrays among processors and structurization of communications

Adutskevich

Likhoded

Sikorsky³

2012

Cybern Syst Anal

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“…The approach to solving the problem of general communication-free data alignment has been developed [4,17,20,23,30]. Most of the methods are based on elementary linear algebra.…”

Section: Introductionmentioning

confidence: 99%

Communication-free data alignment for arrays with exponential references in parallelizing compilers for scalable parallel systems

et al. 2009

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In loops, some arrays are referenced with induction variables. To parallelize such kind of loops, those induction variables should be substituted. Thus, those array references that were substituted are formulated as nonlinear expressions. The goal of data alignment is to intelligently map the computations and data onto a set Communication-free data alignment for arrays with exponential references 5 of virtual processors which are organized as a Cartesian grid (or a template in HPF terms), and to provide data locality for parallelizing compilers so that data access communication costs can be minimized. Most data alignment methods are mainly devised to align the referenced arrays using linear subscripts or quadratic subscripts with n loop index variables, and the methods are well developed. Seldom work, however, is researched on the nonlinear expressions of index variables. This paper proposes a new communication-free data alignment technique to align the referenced arrays using exponential subscripts with n loop index variables or other complex nonlinear expressions. The experimental results using SPEC95FP Benchmarks point out that the techniques proposed in the paper can improve the execution time of the subroutines in these benchmarks.

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“…The data distributions are shown for 3 nodes, each represented by a different shade. The first was generated by our Data Distributor [43]; while the second is the well-known twisted data layout [59]. In each distribution, all four 2D arrays (u, v, p, and q) are distributed as shown in the corresponding figure.…”

Section: An Example Of Adimentioning

confidence: 99%

“…Data distribution (step 1) uses an affinity graph [43] produced by instrumenting the program and then partitioning the graph using Metis [26] . To break the program into subcomputations (step 2) we rely on the well-known techniques of tiling [23,24,52,67,68].…”

Section: Research Motivation and Target Problemmentioning

confidence: 99%