M. Tan et Hj. Siegel, A STOCHASTIC-MODEL FOR HETEROGENEOUS COMPUTING AND ITS APPLICATION INDATA RELOCATION SCHEME DEVELOPMENT, IEEE transactions on parallel and distributed systems, 9(11), 1998, pp. 1088-1101
Citations number
28
Categorie Soggetti
Computer Science Theory & Methods","Engineering, Eletrical & Electronic","Computer Science Theory & Methods
In a dedicated, mixed-machine, heterogeneous computing (HC) system, an
application program may be decomposed into subtasks, then each subtas
k assigned to the machine where it is best suited for execution. Data
relocation is defined as selecting the sources for needed data items.
It is assumed that multiple independent subtasks of an application pro
gram can be executed concurrently on different machines whenever possi
ble. A theoretical stochastic model for HC is proposed, in which the c
omputation times of subtasks and communication times for intermachine
data transfers can be random variables. The optimization problem for f
inding the optimal matching, scheduling, and data relocation schemes t
o minimize the total execution time of an application program is defin
ed based on this stochastic HC model. The global optimization criterio
n and search space for the above optimization problem are described. I
t is validated that a greedy algorithm-based approach can establish a
local optimization criterion for developing data relocation heuristics
. The validation is provided by a theoretical proof based on a set of
common assumptions about the underlying HC system and application prog
ram. The local optimization criterion established by the greedy approa
ch, coupled with the search space defined for choosing valid data relo
cation schemes, can help developers of future practical data relocatio
n heuristics.