Articles with public access mandates - Liu KeLearn more
Available somewhere: 9
Nnest: Early-stage design space exploration tool for neural network inference accelerators
L Ke, X He, X Zhang
Proceedings of the International Symposium on Low Power Electronics and …, 2018
Mandates: US National Science Foundation
AxTrain: Hardware-oriented neural network training for approximate inference
X He, L Ke, W Lu, G Yan, X Zhang
Proceedings of the international symposium on low power electronics and …, 2018
Mandates: National Natural Science Foundation of China
Hercules: Heterogeneity-aware inference serving for at-scale personalized recommendation
L Ke, U Gupta, M Hempstead, CJ Wu, HHS Lee, X Zhang
2022 IEEE International Symposium on High-Performance Computer Architecture …, 2022
Mandates: US National Science Foundation
Menda: A near-memory multi-way merge solution for sparse transposition and dataflows
S Feng, X He, KY Chen, L Ke, X Zhang, D Blaauw, T Mudge, R Dreslinski
Proceedings of the 49th Annual International Symposium on Computer …, 2022
Mandates: US Department of Defense
Neural network-inspired analog-to-digital conversion to achieve super-resolution with low-precision RRAM devices
W Cao, L Ke, A Chakrabarti, X Zhang
2019 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 1-7, 2019
Mandates: US National Science Foundation
Statistical analysis of energy-aware real-time automotive systems in EAST-ADL/Stateflow
EY Kang, J Chen, L Ke, S Chen
2016 IEEE 11th Conference on Industrial Electronics and Applications (ICIEA …, 2016
Mandates: National Natural Science Foundation of China
Evaluating neural network-inspired analog-to-digital conversion with low-precision RRAM
W Cao, L Ke, A Chakrabarti, X Zhang
IEEE Transactions on Computer-Aided Design of Integrated Circuits and …, 2020
Mandates: US National Science Foundation
SecNDP: Secure near-data processing with untrusted memory
W Xiong, L Ke, D Jankov, M Kounavis, X Wang, E Northup, JA Yang, ...
2022 IEEE International Symposium on High-Performance Computer Architecture …, 2022
Mandates: US National Science Foundation
A quantitative exploration of collaborative pruning and approximation computing towards energy efficient neural networks
X He, W Lu, K Liu, G Yan, X Zhang
IEEE Design & Test 37 (1), 36-45, 2019
Mandates: US National Science Foundation, Chinese Academy of Sciences, National …
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