Mantis: Automatic performance prediction for smartphone applications Y Kwon, S Lee, H Yi, D Kwon, S Yang, BG Chun, L Huang, P Maniatis, ...
2013 USENIX Annual Technical Conference (USENIX ATC 13), 297-308, 2013
93 2013 Techniques to minimize state transfer costs for dynamic execution offloading in mobile cloud computing S Yang, D Kwon, H Yi, Y Cho, Y Kwon, Y Paek
IEEE Transactions on Mobile Computing 13 (11), 2648-2660, 2014
78 2014 Fast dynamic execution offloading for efficient mobile cloud computing S Yang, Y Kwon, Y Cho, H Yi, D Kwon, J Youn, Y Paek
2013 IEEE International conference on Pervasive computing and communications …, 2013
55 2013 Precise execution offloading for applications with dynamic behavior in mobile cloud computing Y Kwon, H Yi, D Kwon, S Yang, Y Cho, Y Paek
Pervasive and Mobile Computing 27, 58-74, 2016
32 2016 Mantis: Efficient predictions of execution time, energy usage, memory usage and network usage on smart mobile devices Y Kwon, S Lee, H Yi, D Kwon, S Yang, B Chun, L Huang, P Maniatis, ...
IEEE Transactions on Mobile Computing 14 (10), 2059-2072, 2014
22 2014 CMcloud: Cloud platform for cost-effective offloading of mobile applications D Chae, J Kim, J Kim, J Kim, S Yang, Y Cho, Y Kwon, Y Paek
2014 14th IEEE/ACM International Symposium on Cluster, Cloud and Grid …, 2014
22 2014 Quantune: Post-training quantization of convolutional neural networks using extreme gradient boosting for fast deployment J Lee, M Yu, Y Kwon, T Kim
Future Generation Computer Systems 132, 124-135, 2022
20 2022 Microarchitecture-aware code generation for deep learning on single-isa heterogeneous multi-core mobile processors J Park, Y Kwon, Y Park, D Jeon
IEEE Access 7, 52371-52378, 2019
7 2019 LLMem: Estimating GPU Memory Usage for Fine-Tuning Pre-Trained LLMs T Kim, Y Wang, V Chaturvedi, L Gupta, S Kim, Y Kwon, S Ha
arXiv preprint arXiv:2404.10933, 2024
6 2024 CPrune: Compiler-informed model pruning for efficient target-aware DNN execution T Kim, Y Kwon, J Lee, T Kim, S Ha
European Conference on Computer Vision, 651-667, 2022
6 2022 Q-HyViT: Post-training quantization for hybrid vision transformer with bridge block reconstruction J Lee, Y Kwon, J Park, M Yu, S Park, H Song
arXiv preprint arXiv:2303.12557, 2023
5 2023 Tensor slicing and optimization for multicore NPUs R Sousa, M Pereira, Y Kwon, T Kim, N Jung, CS Kim, M Frank, G Araujo
Journal of Parallel and Distributed Computing 175, 66-79, 2023
4 2023 Q-HyViT: Post-Training Quantization of Hybrid Vision Transformers With Bridge Block Reconstruction for IoT Systems J Lee, Y Kwon, S Park, M Yu, J Park, H Song
IEEE Internet of Things Journal, 2024
3 2024 NEST‐C: A deep learning compiler framework for heterogeneous computing systems with artificial intelligence accelerators J Park, M Yu, J Kwon, J Park, J Lee, Y Kwon
ETRI Journal 46 (5), 851-864, 2024
1 2024 A comprehensive evaluation of quantized instruction-tuned large language models: An experimental analysis up to 405b J Lee, S Park, J Kwon, J Oh, Y Kwon
arXiv preprint arXiv:2409.11055, 2024
1 2024 ACLTuner: A Profiling-Driven Fast Tuning to Optimized Deep Learning Inference Y Kwon, JH Cha, J Lee, M Yu, J Park, J Lee
Proceedings of the Machine Learning for Systems Workshop at NeurIPS, New …, 2023
1 2023 PartitionTuner: An operator scheduler for deep‐learning compilers supporting multiple heterogeneous processing units M Yu, Y Kwon, J Lee, J Park, J Park, T Kim
ETRI Journal 45 (2), 318-328, 2023
1 2023 QuantuneV2: Compiler-based local metric-driven mixed precision quantization for practical embedded AI applications J Kim, J Lee, Y Kwon, D Kim
Future Generation Computer Systems, 107718, 2025
2025 Correction to “NEST‐C: A deep learning compiler framework for heterogeneous computing systems with artificial intelligence accelerators” J Park, M Yu, J Kwon, J Park, J Lee, Y Kwon
ETRI Journal 46 (6), 1126-1126, 2024
2024 ML JH Cha, M Lee, J Kwon, J Lee, J Lee, Y Kwon
arXiv preprint arXiv:2411.10764, 2024
2024 