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检索条件"主题词=Multi-threaded computing"

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A Distributed multithreaded Evolutionary computing Frame Work using Differential Evolution Algorithm 6

A Distributed Multithreaded Evolutionary Computing Frame Wor...

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6th International Conference on Inventive Computation Technologies (ICICT)

作者： Raghul, S. Jeyakumar, G. Amrita Vishwa Vidyapeetham Dept Comp Sci & Engn Amrita Sch Engn Coimbatore Tamil Nadu India

ISBN: (纸本)9781728185019

Differential Evolution (DE), the evolution algorithm (EA) in the repository of evolutionary computing (EC), is known for its simplicity and adaptability to high performance computing paradigms. The distributed algorithmic frameworks of DE are the natural extension of DE, as DE is highly suitable for parallel and distributed computing. This paper proposes a study on implementing an enhanced distributed differential algorithm framework (named as mtdDE - multithreaded distributed DE) with multi-threaded islands in a distributed framework, to attain maximum level of data parallelism. The main objective of mtdDE is to reduce the computation time and to improve the solution quality for the targeted optimization problems. This paper presents this study in two phases. The Phase I implements the traditional distributed DE (dDE) framework and compares its performance with a state-of-the-art distributed DE, on a set of 8 benchmarking functions. In Phase IT the proposed mtdDE was implemented and its performance was compared with the dDE on a set of 4 benchmarking problems. The performance metrics considered were - the objective function values (ofv), the mean objective function values (mov), the execution time (et) and the average execution time (ad). The results acquired for the performance metrics of the dDE and mtdDE were studied, and the study revealed that the mtdDE outperforms the dDE in terms of both the solution accuracy and the computation time. The detailed discussion about the algorithmic structure, the experimental setup, the results obtained and the comparative study were presented in this paper.

关键词： Evolutionary Algorithm Differential Evolution Distributed Framework multi-threaded computing Island models

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A Survey of High-Performance computing for Software Verification 4th

A Survey of High-Performance Computing for Software Verifica...

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4th International Conference on Tools and Methods of Program Analysis (TMPA)

作者： Zakharov, Ilja Russian Acad Sci Inst Syst Programming Moscow Russia

ISBN: (纸本)9783319717340;9783319717333

Automatic software verification is a high-demanded method for software quality assurance since it allows to prove the correctness of programs formally. However, any precise software verification technique requires a considerable amount of computational resources like memory and CPU time. Existing hardware architectures like multi-core CPUs distributed systems, clouds and GPUs can impressively boost verification performance. Developers of verification tools have to adapt their algorithms to modern hardware peculiarities for its productive employment. In the survey, we consider case studies of high-performance computing for speeding up and scaling verification of programs and program models.

关键词： Software verification Cloud computing multi-threaded computing GPU computing Scalability

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Improving Artificial-Immune-System-Based computing by Exploiting Intrinsic Features of Computer Architectures

Improving Artificial-Immune-System-Based Computing by Exploi...

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IEEE Symposium Series on Computational Intelligence (IEEE SSCI)

作者： Deng, Yiqi Bentley, Peter J. Momshad, Alvee UCL Dept Comp Sci London England

ISBN: (纸本)9781509042401

Biological systems have become highly significant for traditional computer architectures as examples of highly complex self-organizing systems that perform tasks in parallel with no centralized control. However, few researchers have compared the suitability of different computing approaches for the unique features of Artificial Immune Systems (AIS) when trying to introduce novel computing architectures, and few consider the practicality of their solutions for real world machine learning problems. We propose that the efficacy of AIS-based computing for tackling real world datasets can be improved by the exploitation of intrinsic features of computer architectures. This paper reviews and evaluates current existing implementation solutions for AIS on different computing paradigms and introduces the idea of "C Principles" and "A Principles". Three Artificial Immune Systems implemented on different architectures are compared using these principles to examine the possibility of improving AIS through taking advantage of intrinsic hardware features.

关键词： Artificial Immune Systems Systemic computing multi-threaded computing

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Improving Artificial-Immune-System-Based computing by Exploiting Intrinsic Features of Computer Architectures

Improving Artificial-Immune-System-Based Computing by Exploi...

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IEEE Symposium Series on Computational Intelligence

作者： Yiqi Deng Peter J. Bentley Alvee Momshad Dept. of Computer Science University College London United Kingdom

ISBN: (纸本)9781509042418

关键词： Artificial Immune Systems Systemic computing multi-threaded computing

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computing Parallel Speeded-Up Robust Features (P-SURF) via POSIX Threads

Computing Parallel Speeded-Up Robust Features (P-SURF) via P...

引用

5th International Conference on Intelligent computing

作者： Zhang, Nan Xian Jiaotong Liverpool Univ Dept Comp Sci & Software Engn Xian Peoples R China

ISBN: (纸本)9783642040696

Speeded-Up Robust Features (SURF);an image local feature extracting and describing method, finds and describes point correspondences between images with different viewing conditions. Despite the fact that it has recently been developed;SURF leas already successfully found its applications in the area of computer vision, and was reported to be more appealing than the earlier Scale-Invariant Feature Transform (SIFT) in terms of robustness and performance. This paper presents a multi-threaded algorithm and its implementation that computes the same SURF. The algorithm parallelises several stages of computations in the original, sequential design. The main benefit brought;about;is the acceleration in computing the descriptor. Tests have been performed to show that the parallel SURF (P-SURF) generally shortened the computation time by a factor of 2 to 6 than the original;sequential method when running on multi-core processors.

关键词： Parallel programming multi-threaded computing Image processing Local feature extraction Machine intelligence

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