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首页> 外文期刊>Journal of supercomputing >SMOaaS: a Scalable Matrix Operation as a Service model in Cloud
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SMOaaS: a Scalable Matrix Operation as a Service model in Cloud

机译：smoaas：可扩展的矩阵操作作为云中的服务模型

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摘要

Matrix operations are fundamental to a wide range of scientific applications such as Graph Theory, Linear Equation System, Image Processing, Geometric Optics, and Probability Analysis. As the workload in these applications has increased, the sizes of matrices involved have also significantly increased. Parallel execution of matrix operations in existing cluster-based systems performs effectively for relatively small matrices but significantly suffers as matrices become larger due to limited resources. Cloud Computing offers scalable resources to handle this limitation; however, the benefits of having access to almost-infinite scalable resources in the Cloud also come with challenges of ensuring time and resource-efficient matrix operations. To the best of our knowledge, there is no specific Cloud service that optimizes the efficiency of matrix operations on Cloud infrastructure. To address this gap and offer convenient service of matrix operations, the paper proposes a novel scalable service framework called Scalable Matrix Operation as a Service. Our framework uses Dynamic Matrix Partition techniques, based on matrix operation and sizes, to achieve efficient work distribution, and scales based on demand to achieve time and resource-efficient operations. The framework also embraces the basic features of security, fault tolerance, and reliability. Experimental results show that the adopted dynamic partitioning technique ensures faster and better performance when compared to the existing static partitioning technique.
机译：矩阵操作是各种科学应用的基础，如图形理论，线性方程系统，图像处理，几何光学和概率分析。随着这些应用中的工作量增加，所涉及的矩阵的大小也显着增加。基于群集的系统中的矩阵操作的并行执行有效地执行相对较小的矩阵，但由于资源有限而矩阵变大，因此显着遭受。云计算提供可扩展资源来处理此限制;但是，在云中访问近几乎无限可扩展的资源的好处也具有确保时间和资源有效的矩阵操作的挑​​战。据我们所知，没有特定的云服务，可以优化云基础架构矩阵操作的效率。为了解决这一差距并提供方便的矩阵操作服务，该文件提出了一种称为可扩展矩阵操作的新型可扩展服务框架作为服务。我们的框架基于矩阵操作和大小使用动态矩阵分区技术，以实现高效的工作分配，并基于需求实现时间和资源有效的操作。该框架还包含安全性，容错和可靠性的基本功能。实验结果表明，与现有的静态分区技术相比，采用的动态分区技术可确保更快，更好的性能。

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