| Summarizing CPU and GPU design trends with product data Y Sun, NB Agostini, S Dong, D Kaeli arXiv preprint arXiv:1911.11313, 2019 | 104 | 2019 |
| MGPUSim: Enabling Multi-GPU Performance Modeling and Optimization Y Sun, T Baruah, SA Mojumder, S Dong, X Gong, S Treadway, Y Bao, ... Proceedings of the 46th International Symposium on Computer Architecture, 2019 | 93 | 2019 |
| Dnnmark: A deep neural network benchmark suite for gpus S Dong, D Kaeli Proceedings of the General Purpose GPUs, 63-72, 2017 | 66 | 2017 |
| Evaluating performance tradeoffs on the radeon open compute platform Y Sun, S Mukherjee, T Baruah, S Dong, J Gutierrez, P Mohan, D Kaeli 2018 IEEE international symposium on performance analysis of systems and …, 2018 | 44 | 2018 |
| GNNMark: A Benchmark Suite to Characterize Graph Neural Network Training on GPUs T Baruah, K Shivdikar, S Dong, Y Sun, SA Mojumder, K Jung, JL Abellan, ... IEEE International Symposium on Performance Analysis of Systems and Software, 2021 | 30 | 2021 |
| Characterizing the Microarchitectural Implications of a Convolutional Neural Network (CNN) Execution on GPUs S Dong, X Gong, Y Sun, T Baruah, D Kaeli ACM International Conference on Performance Engineering, 2018 | 26 | 2018 |
| Airavat: Improving Energy Efficiency of Heterogeneous Applications T Baruah, Y Sun, S Dong, D Kaeli, N Rubin Design Automation and Test in Europe, 2018 | 17 | 2018 |
| Design space exploration of accelerators and end-to-end DNN evaluation with TFLITE-SOC NB Agostini, S Dong, E Karimi, MT Lapuerta, J Cano, JL Abellán, D Kaeli 2020 IEEE 32nd International Symposium on Computer Architecture and High …, 2020 | 15 | 2020 |
| Mgsim+ mgmark: A framework for multi-gpu system research Y Sun, T Baruah, SA Mojumder, S Dong, R Ubal, X Gong, S Treadway, ... arXiv preprint arXiv:1811.02884, 2018 | 14 | 2018 |
| A Hybrid Approach to Identifying Key Factors in Environmental Health Studies S Dong, Z Feric, X Li, SM Rahman, G Li, C Wu, AZ Gu, J Dy, D Kaeli, ... 2018 IEEE International Conference on Big Data (Big Data), 2855-2862, 2018 | 9 | 2018 |
| Spartan: A Sparsity-Adaptive Framework to Accelerate Deep Neural Network Training on GPUs S Dong, Y Sun, NB Agostini, E Karimi, D Lowell, J Zhou, J Cano, ... IEEE Transactions on Parallel and Distributed Systems, 2021 | 7 | 2021 |
| Vcsr: An efficient gpu memory-aware sparse format E Karimi, NB Agostini, S Dong, D Kaeli IEEE Transactions on Parallel and Distributed Systems 33 (12), 3977-3989, 2022 | 6 | 2022 |
| Exploring GPU acceleration of Deep Neural Networks using Block Circulant Matrices S Dong, P Zhao, X Lin, D Kaeli Parallel Computing 100 (ISSN 0167-8191), 2020 | 6 | 2020 |
| An interactive big data processing/visualization framework M Jorgensen, J Spohn, C Bunn, S Dong, X Li, D Kaeli 2017 IEEE MIT Undergraduate Research Technology Conference (URTC), 1-4, 2017 | 6 | 2017 |
| Using Undersampling with Ensemble Learning to Identify Factors Contributing to Preterm Birth S Dong, Z Feric, G Li, C Wu, AZ Gu, J Dy, J Meeker, IY Padilla, J Cordero, ... 19th IEEE International Conference on Machine Learning and Applications, 2020 | 2 | 2020 |
| Data Sparsity Monitoring During Neural Network Training S Dong, D Lowell US Patent 11,562,248, 2020 | 2 | 2020 |
| An Efficient Data Management Framework for Puerto Rico Testsite for Exploring Contamination Threats (PROTECT) S Dong, Z Feric, L Yu, D Kaeli, J Meeker, IY Padilla, J Cordero, CV Vega, ... 2018 IEEE International Conference on Big Data (Big Data), 5316-5318, 2018 | 2 | 2018 |
| Vega: A Computer Vision Processing Enhancement Framework with Graph-based Acceleration J Gutierrez, S Dong, D Kaeli the Hawaii International Conference on System Sciences (HICSS-53), 2020 | 1 | 2020 |
| Exploring High Performance Deep Neural Networks on GPUs S Dong Northeastern University, 2020 | | 2020 |
| MGSim: A Flexible High-Performance Simulator for Multi-GPU Systems Y Sun, T Baruah, S Dong, D Kaeli 9th International Workshop on OpenCL, 2019 | | 2019 |
David R. KaeliDistinguished Professor of ECE, Northeastern UniversityVerified email at ece.neu.edu
