Titlebook: Algorithms and Architectures for Parallel Processing; 20th International C Meikang Qiu Conference proceedings 2020 Springer Nature Switzerl

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MELD

Design of a Convolutional Neural Network Instruction Set Based on RISC-V and Its Microarchitecture Iur work on the broadly used CNN model, LeNet-5, on Field Programmable Gate Arrays (FPGA) for the correctness validation. Comparing to traditional x86 and MIPS ISAs, our design provides a higher code density and performance efficiency.

Gerontology

arbovirus

QoS-Aware and Fault-Tolerant Replica Placementient heuristic algorithms. Finally the proposed algorithms are evaluated with extensive network configurations and the experimental results show that the proposed heuristic algorithms can generate solutions very close to the optimal results.

exorbitant

土产

A Novel Clustering-Based Filter Pruning Method for Efficient Deep Neural Networkss of our approach with several network models, including VGG and ResNet. Experimental results show that on CIFAR-10, our method reduces inference costs for VGG-16 by up to 44% and ResNet-32 by up to 50%, while the accuracy can regain close to the original level.

Vldl379

defuse

https://doi.org/10.1007/978-3-662-58194-0minal devices. Experiments have revealed the characteristics of components execution in the proposed architecture, showing that the system can improve computing performance under the real-world unstable network environments.

MOT

Edge-Assisted Federated Learning: An Empirical Study from Software Decomposition Perspective We conduct an empirical study on a classic convolutional neural network to validate our framework. Experiments show that this method can effectively shorten the time cost for mobile terminals to perform local training in the federated learning process.

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