Title | ||
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Distributed Parallel Computing using Navigational Programming: Orchestrating Computations Around Data |
Abstract | ||
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Message Passing (MP) and Distributed Shared Memory (DSM) are the two most common approaches to program- ming on distributed memory systems. MP is difficult to use, while DSM is not scalable. Performance scalabil- ity and ease of programming can be achieved at the same time by using "shared variable programming" and follow- ing the principle of "computation locus following data," which is embodied in our Navigational Programming ap- proach. The implementation of a real-world algorithm, par- allel Cholesky factorization, presented in this paper sup- ports our claim that Navigational Programming is better suited for general purpose distributed programming than either MP or DSM. |
Year | Venue | Keywords |
---|---|---|
2002 | IASTED PDCS | cholesky fac- torization,distributed parallel computing dpc,message passing mp,shared variable sv programming,navigational programming,distributed shared memory dsm,distributed memory,message passing,cholesky factorization,distributed shared memory |
Field | DocType | Citations |
Distributed object,Supercomputer architecture,Data-intensive computing,Shared memory,Computer science,Parallel computing,Distributed memory,Distributed algorithm,Distributed shared memory,Message passing,Distributed computing | Conference | 2 |
PageRank | References | Authors |
0.85 | 14 | 5 |
Name | Order | Citations | PageRank |
---|---|---|---|
Lei Pan | 1 | 29 | 9.49 |
Lubomir Bic | 2 | 332 | 125.18 |
Michael B. Dillencourt | 3 | 498 | 57.58 |
Javid J. Huseynov | 4 | 12 | 2.13 |
Ming Kin Lai | 5 | 20 | 3.71 |