Lu Zhang

Orcid: 0000-0001-5115-4518

Affiliations:
  • Shanghai Jiao Tong University, Shanghai, China


According to our database1, Lu Zhang authored at least 14 papers between 2019 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
Optimizing GPU-Based Graph Sampling and Random Walk for Efficiency and Scalability.
IEEE Trans. Computers, September, 2023

Fargraph+: Excavating the parallelism of graph processing workload on RDMA-based far memory system.
J. Parallel Distributed Comput., July, 2023

FIRST: Exploiting the Multi-Dimensional Attributes of Functions for Power-Aware Serverless Computing.
Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2023

2022
Tapping into NFV Environment for Opportunistic Serverless Edge Function Deployment.
IEEE Trans. Computers, 2022

Performance optimization for cloud computing systems in the microservice era: state-of-the-art and research opportunities.
Frontiers Comput. Sci., 2022

Cloud-Native Server Consolidation for Energy-Efficient FaaS Deployment.
Proceedings of the Network and Parallel Computing, 2022

Excavating the Potential of Graph Workload on RDMA-based Far Memory Architecture.
Proceedings of the 2022 IEEE International Parallel and Distributed Processing Symposium, 2022

Exploring Efficient Microservice Level Parallelism.
Proceedings of the 2022 IEEE International Parallel and Distributed Processing Symposium, 2022

2021
AlphaR: Learning-Powered Resource Management for Irregular, Dynamic Microservice Graph.
Proceedings of the 35th IEEE International Parallel and Distributed Processing Symposium, 2021

Skywalker: Efficient Alias-Method-Based Graph Sampling and Random Walk on GPUs.
Proceedings of the 30th International Conference on Parallel Architectures and Compilation Techniques, 2021

2020
ANT-man: towards agile power management in the microservice era.
Proceedings of the International Conference for High Performance Computing, 2020

2019
Characterizing and orchestrating NFV-ready servers for efficient edge data processing.
Proceedings of the International Symposium on Quality of Service, 2019

Excavating the Potential of GPU for Accelerating Graph Traversal.
Proceedings of the 2019 IEEE International Parallel and Distributed Processing Symposium, 2019

Performance of Training Sparse Deep Neural Networks on GPUs.
Proceedings of the 2019 IEEE High Performance Extreme Computing Conference, 2019


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