Explore the efficiency and scalability of the

parallel algorithm.

The

parallel algorithm is an effective way to solve this essential problem.

Parallel algorithm based on GPU also performs well.

However, that approach requires a potentially time-consuming serial RNG process before the

parallel algorithm can begin-limiting performance improvements due to parallelism.

The communication structures of parallel program involve the terminology of

parallel algorithm, parallel processing, distributed processing and huge memory allocation.

In this study, desirability function-based scalarization approach is converted into

parallel algorithm and applied into seven benchmark problems.

Tang Tianbing advocates a parallel GA Framework [12], while Yin Xiang and others propose a multi-task multi-ally problem generating model and

parallel algorithm for solution [13].

To execute programs in parallel, there are certain requirements, such as parallel computers/processors, an operating system (Linux preferred), a high level programming language, such as C or Fortran, the parallel application programming interface (MPI), and above all--a

parallel algorithm.

In our previous work [6], we proposed a

parallel algorithm for the analysis of coupled microstrip structures, i.

A Distributed

Parallel Algorithm for SIFT Feature Extraction, Journal of Computer Research and Development, 49 (5) 1130-1141.

In Section 3, the performance of the proposed

parallel algorithm is investigated by comparing it with the serial CPU algorithm and further with the

parallel algorithm using MPI developed in [33].

it includes low-level technicalities like race conditions, deadlocks, starvation, and nondeterminism, all of which must be taken into consideration in

parallel algorithm design and implementation.