Titlebook: Benchmarking, Measuring, and Optimizing; 14th BenchCouncil In Ana Gainaru,Ce Zhang,Chunjie Luo Conference proceedings 2023 The Editor(s) (i

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978-3-031-31179-6The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl

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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/b/image/183392.jpg

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Phyllis Kanki,Darrell Jay GrimesCs) of LeNet-5 to 4.11G MACs of ResNet-50, the computational cost of image classification has increased by 10,000 times over two decades. On the other hand, it has inevitably brought about an increase in energy consumption, and benchmarking the energy efficiency of the modern AI workloads is also es

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https://doi.org/10.1007/978-1-4614-5719-0performance in IoT settings. The microservices architecture has emerged as a mainstay set of design principles for cloud-hosted, network-facing applications. Their utility as a design pattern for “The Internet of Things” (IoT) is less well understood..We use MSDBench to show the performance impacts

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The Common Infectious Diseases,butes. In order to improve the accuracy of project recommendation, it is necessary to effectively integrate this multi-source information. Therefore, for the project recommendation scenario, this paper defines an open source weighted heterogeneous information network to represent the different entit

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The Common Infectious Diseases,researchers have made persistent efforts to design powerful models. For example, Spatial-Temporal Graph Neural Networks (STGNNs) have become increasingly popular MTS prediction methods due to their state-of-the-art performance. However, we found there exists much unfairness in the comparison of the