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2020 – today
- 2025
[j5]Di Li
, Shirui Tian, Wenqiang Jin, Jiwu Peng, Mingxing Duan:
Towards a moving target defense based on stochastic games and honeypots. Inf. Sci. 720: 122488 (2025)- 2024
- [j4]Longxin Zhang, Runti Tan, Yanfen Zhang, Jiwu Peng, Jing Liu, Keqin Li:
UAV-assisted dependency-aware computation offloading in device-edge-cloud collaborative computing based on improved actor-critic DRL. J. Syst. Archit. 154: 103215 (2024) - 2022
- [j3]Jiwu Peng, Kenli Li, Jianguo Chen, Keqin Li:
HEA-PAS: A hybrid energy allocation strategy for parallel applications scheduling on heterogeneous computing systems. J. Syst. Archit. 122: 102329 (2022) - [j2]Jiwu Peng, Kenli Li, Jianguo Chen, Keqin Li:
Reliability/Performance-Aware Scheduling for Parallel Applications With Energy Constraints on Heterogeneous Computing Systems. IEEE Trans. Sustain. Comput. 7(3): 681-695 (2022) - 2020
- [j1]Linlin Zhuo, Kenli Li, Hao Li, Jiwu Peng, Keqin Li:
An online and generalized non-negativity constrained model for large-scale sparse tensor estimation on multi-GPU. Neurocomputing 399: 18-36 (2020)
2010 – 2019
- 2017
- [c4]Wei Ai, Kenli Li, Cen Chen, Jiwu Peng, Keqin Li:
DHCRF: A Distributed Conditional Random Field Algorithm on a Heterogeneous CPU-GPU Cluster for Big Data. ICDCS 2017: 2372-2379 - [c3]Hao Li, Kenli Li, Jiwu Peng, Junyan Hu, Keqin Li:
An Efficient Parallelization Approach for Large-Scale Sparse Non-Negative Matrix Factorization Using Kullback-Leibler Divergence on Multi-GPU. ISPA/IUCC 2017: 511-518 - [c2]Hao Li, Kenli Li, Jiwu Peng, Keqin Li:
CuSNMF: A Sparse Non-Negative Matrix Factorization Approach for Large-Scale Collaborative Filtering Recommender Systems on Multi-GPU. ISPA/IUCC 2017: 1144-1151 - 2016
- [c1]Jiwu Peng, Zheng Xiao, Cen Chen, Wangdong Yang:
Iterative sparse matrix-vector multiplication on in-memory cluster computing accelerated by GPUs for big data. ICNC-FSKD 2016: 1454-1460
Coauthor Index
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