| GraphH: A Processing-in-Memory Architecture for Large-scale Graph Processing G Dai, T Huang, Y Chi, J Zhao, G Sun, Y Liu, Y Wang, Y Xie, H Yang IEEE Transactions on Computer-Aided Design of Integrated Circuits and …, 2019 | 188* | 2019 |
| ForeGraph: Exploring large-scale graph processing on multi-FPGA architecture G Dai, T Huang, Y Chi, N Xu, Y Wang, H Yang International Symposium on Field-Programmable Gate Arrays (FPGA), 217-226, 2017 | 180 | 2017 |
| FPGP: Graph Processing Framework on FPGA A Case Study of Breadth-First Search G Dai, Y Chi, Y Wang, H Yang International Symposium on Field-Programmable Gate Arrays (FPGA), 105-110, 2016 | 145 | 2016 |
| GE-SpMM: General-purposed Sparse Matrix-Matrix Multiplication on GPUs for Graph Neural Networks G Huang, G Dai, Y Wang, Y Huazhong International Conference for High Performance Computing, Networking, Storage …, 2020 | 128 | 2020 |
| NXgraph: An Efficient Graph Processing System on a Single Machine Y Chi, G Dai, Y Wang, G Sun, G Li, H Yang International Conference on Data Engineering (ICDE), 409-420, 2016 | 103 | 2016 |
| A Configurable Multi-precision CNN Computing Framework based on Single Bit RRAM Z Zhu, H Sun, Y Lin, G Dai, L Xia, S Han, Y Wang, H Yang ACM/IEEE Design Automation Conference (DAC), 1-6, 2019 | 101 | 2019 |
| MNSIM 2.0: A Behavior-Level Modeling Tool for Memristor-based Neuromorphic Computing Systems Z Zhu, H Sun, K Qiu, L Xia, G Krishnan, G Dai, D Niu, X Chen, XS Hu, ... Great Lakes Symposium on VLSI (GLSVLSI), 83-88, 2020 | 79 | 2020 |
| GraphSAR: A Sparsity-aware Processing-in-memory Architecture for Large-scale Graph Processing on ReRAMs G Dai, T Huang, Y Wang, H Yang, J Wawrzynek Asia and South Pacific Design Automation Conference (ASP-DAC), 120-126, 2019 | 57 | 2019 |
| A survey on efficient inference for large language models Z Zhou, X Ning, K Hong, T Fu, J Xu, S Li, Y Lou, L Wang, Z Yuan, X Li, ... arXiv preprint arXiv:2404.14294, 2024 | 56 | 2024 |
| Understanding gnn computational graph: A coordinated computation, io, and memory perspective H Zhang, Z Yu, G Dai, G Huang, Y Ding, Y Xie, Y Wang Proceedings of Machine Learning and Systems 4, 467-484, 2022 | 51 | 2022 |
| FlashDecoding++: Faster Large Language Model Inference with Asynchronization, Flat GEMM Optimization, and Heuristics K Hong, G Dai, J Xu, Q Mao, X Li, J Liu, Y Dong, Y Wang Proceedings of Machine Learning and Systems 6, 148-161, 2024 | 46* | 2024 |
| Dimmining: pruning-efficient and parallel graph mining on near-memory-computing G Dai, Z Zhu, T Fu, C Wei, B Wang, X Li, Y Xie, H Yang, Y Wang Proceedings of the 49th Annual International Symposium on Computer …, 2022 | 44 | 2022 |
| CogDL: An extensive toolkit for deep learning on graphs Y Cen, Z Hou, Y Wang, Q Chen, Y Luo, X Yao, A Zeng, S Guo, P Zhang, ... arXiv preprint arXiv:2103.00959, 2021 | 36 | 2021 |
| Flightllm: Efficient large language model inference with a complete mapping flow on fpgas S Zeng, J Liu, G Dai, X Yang, T Fu, H Wang, W Ma, H Sun, S Li, Z Huang, ... Proceedings of the 2024 ACM/SIGDA International Symposium on Field …, 2024 | 34 | 2024 |
| Evaluating quantized large language models S Li, X Ning, L Wang, T Liu, X Shi, S Yan, G Dai, H Yang, Y Wang arXiv preprint arXiv:2402.18158, 2024 | 29 | 2024 |
| Online Scheduling for FPGA Computation in the Cloud G Dai, Y Shan, F Chen, Y Wang, K Wang, H Yang International Conference on Field-Programmable Technology (FPT), 330-333, 2014 | 29 | 2014 |
| Enabling Efficient and Flexible FPGA Virtualization for Deep Learning in the Cloud S Zeng, G Dai, H Sun, K Zhong, G Ge, K Guo, Y Wang, H Yang International Symposium on Field-Programmable Custom Computing Machines …, 2020 | 26* | 2020 |
| GraphIA: An In-situ Accelerator for Large-scale Graph Processing G Li, G Dai, S Li, Y Wang, Y Xie International Symposium on Memory Systems (MEMSYS), 79-84, 2018 | 24 | 2018 |
| Mnsim 2.0: A behavior-level modeling tool for processing-in-memory architectures Z Zhu, H Sun, T Xie, Y Zhu, G Dai, L Xia, D Niu, X Chen, XS Hu, Y Cao, ... IEEE Transactions on Computer-Aided Design of Integrated Circuits and …, 2023 | 23 | 2023 |
| Rerec: In-reram acceleration with access-aware mapping for personalized recommendation Y Wang, Z Zhu, F Chen, M Ma, G Dai, Y Wang, H Li, Y Chen 2021 IEEE/ACM International Conference On Computer Aided Design (ICCAD), 1-9, 2021 | 22 | 2021 |
Yu Wang (汪玉)Department of Electronic Engineering, Tsinghua University, ChinaVerified email at mail.tsinghua.edu.cn
