Comparison and Analysis of GPGPU and Parallel Computing on Multi-Core CPU

Zhang, Hong; Zhang, Dafang; Bi, Xia-an

doi:10.7763/ijiet.2012.v2.106

Cited by 7 publications

(4 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The author has extensively used the mechanism of parallel computing along with implementation of CPU and GPU [1]. The GPU parallelization has been used to improve the computation of RSA algorithm [2].…”

Section: Discussionmentioning

confidence: 99%

“…GPU is suitable for processing large scale data parallel load of high density computing but relatively simple branching logic and CPU is more suitable for processing complex logic computation. This paper explains the exponentiation for the RSA algorithm through the analysis of GPU implementation and CPU implementation and the result shows that the GPU can achieve more than 45 times speedup in comparison with multicore CPU [1].…”

Section: Related Research Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Cryptographic algorithm on multicore processor: A review

Jain¹,

Sharma²,

Sharma³

2015

2015 International Conference on Advances in Computer Engineering and Applications

View full text Add to dashboard Cite

Cryptography involves different cryptographic algorithm that contributes in the security purpose of the programs. The cryptography algorithms are divided into two parts symmetric and asymmetric. There are many different challenges to implement cryptography algorithm specially throughput in terms of time execution. So, it is important that it runs with minimum encryption and decryption time and hence improvise the time efficiency. In this paper, we study and analyze the performance of different cryptographic algorithm on multicore processors and also we explore the performance in sequential and parallel implementation of cryptography algorithm on multi core processors. In this review paper we have given the summary of different research papers on cryptography and briefed about some cryptographic tools.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Related Research Reviewmentioning

confidence: 99%

Cryptographic algorithm on multicore processor: A review

Jain¹,

Sharma²,

Sharma³

2015

2015 International Conference on Advances in Computer Engineering and Applications

View full text Add to dashboard Cite

show abstract

“…Therefore, there is no need to turn back to DRAM (Dynamic Random Access Memory) for threads which are trying to have an access to data in the same memory area. Thus, results are obtained much faster for any application that has parallelizable functions by running on GPU [42], [43]. CUDA is quite useful and practical thanks to its easy thread management structure and being a software with shared memory that can be used on GPU.…”

Section: Gpu Parallel Computing Architecture and Cuda Programming Modelmentioning

confidence: 99%

High Performance Twitter Sentiment Analysis Using CUDA Based Distance Kernel on GPUs

et al. 2019

View full text Add to dashboard Cite

Sentiment analysis techniques are widely used for extracting feelings of users in different domains such as social media content, surveys, and user reviews. This is mostly performed by using classical text classification techniques. One of the major challenges in this field is having a large and sparse feature space that stems from sparse representation of texts. The high dimensionality of the feature space creates a serious problem in terms of time and performance for sentiment analysis. This is particularly important when selected classifier requires intense calculations as in k-NN. To cope with this problem, we used sentiment analysis techniques for Turkish Twitter feeds using the NVIDIA's CUDA technology. We employed our CUDA-based distance kernel implementation for k-NN which is a widely used lazy classifier in this field. We conducted our experiments on four machines with different computing capacities in terms of GPU and CPU configuration to analyze the impact on speed-up.

show abstract

“…Six years later in 2012, Hong Zhang et al presented "Comparison and Analysis of GPGPU and Parallel Computing on Multi-Core CPU" [12]. They presented in this paper that RSA algorithm is very compute intensive and CPU is not suitable to perform the modular exponentiation part of it.…”

Section: Sh Tang Et Al Presented "Modular Exponentiation Using Parall...mentioning

confidence: 99%