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“…Compared with cationic polyurethane (CPU), ZPU shows similar thermal stability. The physical cross-linking network formed between zwitterion groups can dissipate strain energy as a weak dynamic bond, endowing ZPU with outstanding mechanical and elastic recovery properties, including the high tensile strength of 7.38 MPa, high elongation at a break of 980%, and fast elastic recovery ability. …”
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“…The results of our study provide useful insight for spectroscopists to select an adapted method for structure prediction of carbonyl compounds based on their available computational resources, suggesting a reasonable trade-off between accuracy and CPU cost. At the same time, our observations and the resulting sets of highly accurate experimental constants from high-resolution spectroscopy experiments give an appeal to theoretical groups to look further into this seemingly simple family of chemical compounds, which may prove useful for the further development and parametrization of theoretical methods in computational chemistry.…”
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“…Furthermore, benchmark analysis showed that the Odroid N2+ platform was the most convenient in terms of CPU load, RAM usage, and average execution time of the algorithmic pipeline.…”
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“…Based on this analysis, the decomposed workloads of trackers are multi-threaded under the control of the scheduling framework. CPU-side multi-threading leads the GPU to a work-conserving state while enabling parallel processing as much as possible even within a single GPU depending on the resource availability of the internal hardware. …”
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“…The average detection time per packet is 0.3958 ms with graphics processing unit (GPU) acceleration and 0.6669 ms with only a central processing unit (CPU). After vehicle-level real-time analyses, the proposed IDS can be deployed for distributed or select critical advanced driving assistance system (ADAS) traffic for detection in a centralized layout.…”
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“…If only a traditional software protocol stack is used for processing, it will occupy a large amount of CPU resources and affect network performance. To address the above issues, this paper proposes a double-queue storage structure for a 10G TCP/IP hardware offload engine based on FPGA. …”
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“…We have produced a dataset gathering a large set of features related not only to traffic, but other parameters such as CPU and memory. Furthermore, we provide the network topology of each sample in terms of the adjacency matrix, routing table and routing metrics. …”
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“…It is shown that the second method’s processing time is lower than the video acquisition time with a 1024 × 1024 input on a CPU, which had not been previously achieved. The accuracy it obtained on datasets widely used by the scientific community was almost on par with that obtained using the most-recent state-of-the-art methods using deep learning. …”
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“…Subsequently, we propose a model predictive direct motion control (MPDMC) approach that utilizes a single CPU to directly follow the driver’s commands by generating voltage references with a minimum cost function. …”
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“…In this work, we present a new hybrid CPU-GPU algorithm for the rapid generation of 3D Voronoi diagrams. …”
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“…To address this, this paper designed a novel data-sharing framework (i.e., PPChain) based on blockchain and federated learning. The experiment uses a CPU i7-12800HX and uses Docker to simulate multiple virtual nodes. …”
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“…For application, the TCT maximum temperature state simulation was conducted on a CPU chip. The simulation indicated that for an advanced package, the maximum stress was more likely to occur in RDL rather than in bumps; both RDL and bumps were critically impacted by layouts, and RDL stress was also impacted by vias/bumps. …”
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“…We perform an extensive evaluation of state-of-the-art (SOTA) Deep Neural Networks (DNNs) across multiple compute regimes, finding our method transfers from our camera motion free da Vinci surgery dataset to videos of laparoscopic interventions, outperforming classical homography estimation approaches in both, precision by [Image: see text] , and runtime on a CPU by [Image: see text] .…”
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“…PyMC leverages the symbolic computation library PyTensor, allowing it to be compiled into a variety of computational backends, such as C, JAX, and Numba, which in turn offer access to different computational architectures including CPU, GPU, and TPU. Being a general modeling framework, PyMC supports a variety of models including generalized hierarchical linear regression and classification, time series, ordinary differential equations (ODEs), and non-parametric models such as Gaussian processes (GPs). …”
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“…To improve the performance of tools that accomplish these tasks, Machine Learning approaches (ML) that leverage computer resources, such as GPUs (Graphical Processing Unit) and multiple CPU (Central Processing Unit) cores, have been adopted. …”
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“…A measure of the computational cost shows that our proposal can be employed in real-time (about 100 frame-per-second on GPU) and in quasi-real-time (about 7/8 frame-per-second on CPU) visual-based apple inspection. To further improve the applicability of the method, we investigate the potential of using only RGB images instead of multi-spectral images as input images. …”
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“…Compared with HFSS software, the proposed model can save about 70% CPU time in predicting a set of 100 data. The results show that the proposed method achieves a good modeling accuracy and efficiency with few training data and a low computational cost.…”
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“…The final set presents benchmarking data generated by scaling out the QE's model across 32 nodes (1,536 CPU cores) on the NCI Gadi supercomputer. Despite its focus on a single material, the dataset serves as a roadmap for researchers to estimate required computational resources and understand scalability bottlenecks, offering general guidelines adaptable across different HPC systems.…”
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