Abstract:
Power-performance tradeoff is a critical issue in the heterogeneous multiprocessor system, especially, in the modern mobile computers with large
number of cores. Task scheduling in heterogeneous multiprocessor systems is
defined as NP-complete problem. Which means the optimum power and execution time could not be achieved using some known algorithm in polynomial
time. A heterogeneous multiprocessor system needs a complex algorithm to
achieve a sub-optimal power and performance when executing a given application.
In this thesis we introduce a powerful methodology for exploring the valid
combinations of heterogeneous processors in multi processors platforms with
large number of processors to execute a given application with the purpose of
achieving the suitable power-performance tradeoff. Our methodology employs
the genetic algorithms (GAs) to explore the search space of valid combinations
of the processors to execute the problem.
The experimental results show that our objectives regarding the performancepower enhancement are achieved. Moreover, we succeed in estimating the time
and power needed to execute a big problem among high scale processors in of-
:fline mode. Accordingly, the suitable processors configuration is set to achieve
the maximum performance within the consuming power constraint by using
GA.
Description:
no of pages 149, 27259, informatics 3/2012 , in the store
