(2015) presented a

parallel algorithm to handle the RSA decryption by investigating the effect of Pthread and computing a unified device architecture (CUDA) on decryption operation in RSA cryptosystem.

Using a varying number of data size and clusters, the results prove that the

parallel algorithm achieves more efficiency and time complexity than the sequential algorithm.

With the new extensive

parallel algorithm also providing much larger capacity than before, any full-chip SoC designs can now be run flat, not only for power-grid IR drop and electromigration (EM) analysis but also electrical and thermal co-analysis at the chip-package-board system level, including 3DIC, with Cadence Sigrity technologies.

(3) In order to improve the speed of the semantic compression algorithm, we use the CUDA kernel function to implement the parallel computation of the optimized iterative semantic compression algorithm on the GPU, and propose the GPU

parallel algorithm POICAG (Parallel Optimized Iterative Compression Algorithm Using GPU).

For this reason, Ottoni proposed an instruction-level automatic task

parallel algorithm called Decoupled Software Pipelines (DSWP) [4].

The running times required by the Canny and Otsu-Canny algorithm in the literature [21] are much longer than those of the parallel Canny algorithm and the

parallel algorithm proposed in this study and become dramatically longer as the number of images increases because the

parallel algorithm adopts the distributed parallel processing technology of the MapReduce framework in the Hadoop platform, whereas the Canny and Otsu-Canny algorithm in the literature [18] use a single-node architecture with limited processing capacity.

A study in 2009 considered computing a noise map on a supercomputer; in this effort, software called Noise Propagation Model is used to obtain the noise map in a supercomputer [26]; the

parallel algorithm assigns tasks at one time rather than using dynamic assignment, and the noise map is two-dimensional.

It can be observed from Figure 5 that the

parallel algorithm based on the PISO numerical scheme demonstrates significantly better parallel scalability and efficiency than the

parallel algorithm based on the coupled numerical scheme.

The Embarrassingly

Parallel Algorithm (EPA) implemented is shown in figure 3.

This paper proposes a combined

parallel algorithm named "CZ algorithm" to compress and encrypt the big data efficiently.

In order to examine the performance of

parallel algorithm, a standard benchmark data is used which is represented the common used of string matching algorithm, which are English text, Proteins sequence and DNA sequence.

The

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