Beilei Jiang

Previous Scheduled Teaching

Published Intellectual Contributions

Conference Proceeding

• Jiang, B., Cheng, X., Li, Y., Fu, S., Yang, Q., Liu, M., Olvera, A. (2023). Output-Directed Dynamic Quantization for DNN Acceleration. 645-654. International Conference on Parallel Processing (ICPP).
• Jiang, B., Cheng, X., Tang, S., Ma, X., Gu, Z., Fu, S., Yang, Q., Liu, M. (2022). MLCNN: Cross-Layer Cooperative Optimization and Accelerator Architecture for Speeding Up Deep Learning Applications.. International Parallel and Distributed Processing Symposium (IPDPS. 1184-1194. https://ieeexplore.ieee.org/abstract/document/9820611
• Gu, Z., Tang, S., Jiang, B., Huang, S., Guan, Q., Fu, S. (2021). Characterizing Job-Task Dependency in Cloud Workloads Using Graph Learning. 2021 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW). https://ieeexplore.ieee.org/abstract/document/9460684
• Jiang, B., Cheng, X., Tang, S., Ma, X., Gu, Z., Zhao, H., Fu, S. (2021). APCNN: Explore Multi-Layer Cooperation for CNN Optimization and Acceleration on FPGA. The 2021 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays. https://dl.acm.org/doi/abs/10.1145/3431920.3439461
• Cheng, X., Zhao, H., Kandemir, M., Jiang, B., Mehta, G. (2020). AMOEBA: a coarse-grained reconfigurable architecture for dynamic GPU scaling. The 34th ACM International Conference on Supercomputing. https://dl.acm.org/doi/abs/10.1145/3392717.3392738
• Cheng, X., Zhao, H., Kandemir, M., Mohanty, S., Jiang, B. (2020). Alleviating Bottlenecks for DNN Execution on GPUs via Opportunistic Computing. 2020 21st International Symposium on Quality Electronic Design (ISQED). https://ieeexplore.ieee.org/abstract/document/9136967
• Cheng, X., Zhao, Y., Robaei, M., Jiang, B., Zhao, H., Fang, J. (2019). A low-cost and energy-efficient noc architecture for GPGPUs. ACM/IEEE Symposium on Architectures for Networking and Communications Systems (ANCS).