Shi Dong
Shi Dong
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Dnnmark: A deep neural network benchmark suite for gpus
S Dong, D Kaeli
Proceedings of the General Purpose GPUs, 63-72, 2017
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
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
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
Summarizing cpu and gpu design trends with product data
Y Sun, NB Agostini, S Dong, D Kaeli
arXiv preprint arXiv:1911.11313, 2019
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
Airavat: Improving Energy Efficiency of Heterogeneous Applications
T Baruah, Y Sun, S Dong, D Kaeli, N Rubin
Design Automation and Test in Europe, 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
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
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
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
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
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
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
Data Sparsity Monitoring During Neural Network Training
S Dong, D Lowell
US Patent App. 16/397,283, 2020
Design Space Exploration of Accelerators and End-to-End DNN Evaluation with TFLITE-SOC
N Bohm Agostini, S Dong, K Elmira, TL Marti, J Cano, JL Abellán, D Kaeli
SBAC-PAD, 10-19, 2020
Exploring GPU acceleration of Deep Neural Networks using Block Circulant Matrices
S Dong, P Zhao, X Lin, D Kaeli
Parallel Computing, 2020
Exploring High Performance Deep Neural Networks on GPUs
S Dong
Northeastern University, 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
Interactive Kernel Dimension Alternative Clustering on GPUs
X Li, C Wu, S Dong, J Dy, D Kaeli
2018 IEEE/ACM International Conference on Advances in Social Networks …, 2018
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