( en | de | ru )

 

Disambiguation

From post

копироватьудалитьдобавить публикацию в буфер
vTensor: Flexible Virtual Tensor Management for Efficient LLM Serving.

, , , , , , , , , , , , , и . CoRR, (2024)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed.

Shixuan Pang

Yü-Sün Sun

Hongqing Sun

Guolin Sun

Han Sun

 

Другие публикации лиц с тем же именем

Scaling Up Subgraph Query Processing with Efficient Subgraph Matching., и . ICDE, стр. 220-231. IEEE, (2019)FlowWalker: A Memory-efficient and High-performance GPU-based Dynamic Graph Random Walk Framework., , , , , , , , , и 2 other автор(ы). Proc. VLDB Endow., 17 (8): 1788-1801 (апреля 2024)FaaSGraph: Enabling Scalable, Efficient, and Cost-Effective Graph Processing with Serverless Computing., , , , , , , и . ASPLOS (2), стр. 385-400. ACM, (2024)In-Memory Subgraph Matching: An In-depth Study., и . SIGMOD Conference, стр. 1083-1098. ACM, (2020)Cache-Efficient Fork-Processing Patterns on Large Graphs., , , , и . SIGMOD Conference, стр. 1208-1221. ACM, (2021)RUSH: Real-time Burst Subgraph Discovery in Dynamic Graphs., , , , и . Proc. VLDB Endow., 17 (11): 3657-3665 (июля 2024)Parallelizing Pruning-based Graph Structural Clustering., , и . ICPP, стр. 77:1-77:10. ACM, (2018)Efficient Deep Learning Pipelines for Accurate Cost Estimations Over Large Scale Query Workload., , , , , и . SIGMOD Conference, стр. 1014-1022. ACM, (2021)ThunderRW: An In-Memory Graph Random Walk Engine (Complete Version)., , , , и . CoRR, (2021)Async-fork: Mitigating Query Latency Spikes Incurred by the Fork-based Snapshot Mechanism from the OS Level., , , , , , , , , и 5 other автор(ы). Proc. VLDB Endow., 16 (5): 1033-1045 (2023)