Background:
Embedded multi-core systems often have special limitations in sharing
resources and storage capacity. These limitations often lead to parallel programs
running with lower parallel efficiency due to bandwidth, data competition and other
factors.
Objective:
In order to improve the performance of embedded multi-core systems,
parallel strategies can be adjusted dynamically and adaptively for different parallel
program structures.
Method:
A control mechanism of the thread count based on runtime information
feedback is proposed, which enables the system to dynamically select the number of
threads when the program runs best according to the structure characteristics of
parallel programs. Then, an adaptive dynamic scheduling algorithm is proposed to
solve the load imbalance in parallel program execution.
Results:
An optimization framework based on run-time architecture is presented,
which consists of two parts: performance monitoring and control interface. It can take
corresponding optimization strategies according to the running state of parallel
programs.
Conclusion:
The performance of embedded multi-core system is improved.
