Ruiqing Cheng

most citedFirst-principles Prediction of Potential Candidate Materials MCu

_{3}

_{4}

(M = V, Nb, Ta; X = S, Se, Te) for Neuromorphic Computing

4 citations · 6 across the 2 of their papers we have counts for

collaborators

2 papers

cond-mat.mtrl-sci2023★ 4 cited

First-principles Prediction of Potential Candidate Materials MCu $_{3}$ X $_{4}$ (M = V, Nb, Ta; X = S, Se, Te) for Neuromorphic Computing

Baoxing Zhai, Ruiqing Cheng, Tianxing Wang +6

Inspired by the neuro-synaptic frameworks in the human brain, neuromorphic computing is expected to overcome the bottleneck of traditional von-Neumann architecture and be used in a…

eess.SY2021★ 2 cited

An Optimal Resource Allocator of Elastic Training for Deep Learning Jobs on Cloud

Liang Hu, Jiangcheng Zhu, Zirui Zhou +3

Cloud training platforms, such as Amazon Web Services and Huawei Cloud provide users with computational resources to train their deep learning jobs. Elastic training is a service e…

First-principles Prediction of Potential Candidate Materials MCu3​X4​ (M = V, Nb, Ta; X = S, Se, Te) for Neuromorphic Computing

An Optimal Resource Allocator of Elastic Training for Deep Learning Jobs on Cloud

First-principles Prediction of Potential Candidate Materials MCu $_{3}$ X $_{4}$ (M = V, Nb, Ta; X = S, Se, Te) for Neuromorphic Computing