Title
Distributed Parallel Computing using Navigational Programming: Orchestrating Computations Around Data
Abstract
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 Pan1299.49
Lubomir Bic2332125.18
Michael B. Dillencourt349857.58
Javid J. Huseynov4122.13
Ming Kin Lai5203.71