| Evaluating the energy efficiency of deep convolutional neural networks on CPUs and GPUs D Li, X Chen, M Becchi, Z Zong 2016 IEEE international conferences on big data and cloud computing (BDCloud …, 2016 | 214 | 2016 |
| Deploying Graph Algorithms on GPUs: an Adaptive Solution D Li, M Becchi 2013 IEEE 27th International Symposium on Parallel & Distributed Processing …, 2013 | 54 | 2013 |
| Compiler-assisted Workload Consolidation for Efficient Dynamic Parallelism on GPU H Wu, D Li, M Becchi 2016 IEEE 27th International Symposium on Parallel & Distributed Processing …, 2016 | 32 | 2016 |
| Learning convolution neural networks on heterogeneous cpu-gpu platform M Liu, X Xu, D Li US Patent 10,002,402, 2018 | 29 | 2018 |
| Nested Parallelism on GPU: Exploring Parallelization Templates for Irregular Loops and Recursive Computations D Li, H Wu, M Becchi International Conference on Parallel Processing, 2015 | 27 | 2015 |
| Multiple pairwise sequence alignments with the needleman-wunsch algorithm on gpu D Li, M Becchi 2012 SC companion: high performance computing, networking storage and …, 2012 | 21 | 2012 |
| A Distributed CPU-GPU Framework for Pairwise Alignments on Large-Scale Sequence Datasets D Li, K Sajjapongse, H Truong, G Conant, M Becchi 2013 IEEE 24th International Conference on Application-Specific Systems …, 2013 | 20 | 2013 |
| Large-Scale Pairwise Alignments on GPU Clusters: Exploring the Implementation Space H Truong, D Li, K Sajjapongse, G Conant, M Becchi Journal of Signal Processing Systems 77 (1-2), 131-149, 2014 | 12 | 2014 |
| GRapid: a Compilation and Runtime Framework for Rapid Prototyping of Graph Applications on Many-core Processors D Li, S Chakradhar, M Becchi 2014 IEEE 20th International Conference on Parallel and Distributed Systems, 2014 | 12 | 2014 |
| Exploiting dynamic parallelism to efficiently support irregular nested loops on GPUs D Li, H Wu, M Becchi Proceedings of the 2015 International Workshop on Code Optimisation for …, 2015 | 9 | 2015 |
| Source-to-source transformations for graph processing on many-core platforms S Chakradhar, M Becchi, D Li US Patent 20,150,113,514, 2016 | 7 | 2016 |
| Fast integral histogram computations on GPU for real-time video analytics M Poostchi, K Palaniappan, D Li, M Becchi, F Bunyak, G Seetharaman arXiv preprint arXiv:1711.01919, 2017 | 6 | 2017 |
| GTF: An Adaptive Network Anomaly Detection Method at the Network Edge R Li, Z Zhou, X Liu, D Li, W Yang, S Li, Q Liu Security and Communication Networks 2021 (1), 3017797, 2021 | 4 | 2021 |
| BPA:The Optimal Placement of Interdependent VNFs in Many-core System Y Zhong, Z Zhou, X Liu, D Li, M Guo, S Zhang, Q Liu, L Guo EAI CollaborateCom, 2020 | 3 | 2020 |
| Multi-source data oriented flexible real-time information fusion platform on FPGA T Song, D Li, Y Yao 2011 International Conference on Electronics, Communications and Control …, 2011 | 2 | 2011 |
| A Scalable Cloud-based Architecture to Deploy JupyterHub for Computational Social Science Research D Li, R Pyke, R Jiang Practice and Experience in Advanced Research Computing, 2021 | 1 | 2021 |
| Facilitating emerging applications on many-core processors D Li University of Missouri--Columbia, 2016 | 1 | 2016 |
| Designing Code Variants for Applications with Nested Parallelism on GPUs D Li, M Becchi GPU Technology Conference, 2015 | 1* | 2015 |
| SASD: A Self-Adaptive Stateful Decompression Architecture Z Zhou, X Zhang, Q Kiu, Y Zhu, D Li, L Guo IEEE Global Communications Conference, 2018 | | 2018 |
| 一种搜索引擎中的多字符串匹配方法 T Song, D Li CN Patent CN101,901,257 B, 2012 | | 2012 |
Michela BecchiNorth Carolina State UniversityVerified email at ncsu.edu
