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检索条件"机构=Service Computing Technology and System Lab./Cluster and Grid Computing Lab."
126 条 记 录,以下是1-10 订阅
排序:
AegonKV: A High Bandwidth, Low Tail Latency, and Low Storage Cost KV-Separated LSM Store with SmartSSD-based GC Offloading  23
AegonKV: A High Bandwidth, Low Tail Latency, and Low Storage...
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23rd USENIX Conference on File and Storage Technologies, FAST 2025
作者: Duan, Zhuohui Feng, Hao Liu, Haikun Liao, Xiaofei Jin, Hai Li, Bangyu National Engineering Research Center for Big Data Technology and System Service Computing Technology and System Lab/Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology China
The key-value separation is renowned for its significant mitigation of the write amplification inherent in traditional LSM trees. However, KV separation potentially increases performance overhead in the management of ... 详细信息
来源: 评论
High-Performance and Resource-Efficient Dynamic Memory Management in High-Level Synthesis  24
High-Performance and Resource-Efficient Dynamic Memory Manag...
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61st ACM/IEEE Design Automation Conference, DAC 2024
作者: Wang, Qinggang Zheng, Long An, Zhaozeng Huang, Haoqin Zhu, Haoran Huang, Yu Yao, Pengcheng Liao, Xiaofei Jin, Hai National Engineering Research Center for Big Data Technology and System Service Computing Technology and System Lab Cluster and Grid Computing Lab Huazhong University of Science and Technology Wuhan China Zhejiang Lab Hangzhou China
With the merits of high productivity and ease of use, highlevel synthesis (HLS) tools bring hope to fast FPGA-based architecture development. However, their usability and popularity are still limited due to lack of su... 详细信息
来源: 评论
RTGA: A Redundancy-free Accelerator for High-Performance Temporal Graph Neural Network Inference  24
RTGA: A Redundancy-free Accelerator for High-Performance Tem...
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61st ACM/IEEE Design Automation Conference, DAC 2024
作者: Yu, Hui Zhang, Yu Tan, Andong Lu, Chenze Zhao, Jin Liao, Xiaofei Jin, Hai Liu, Haikun National Engineering Research Center for Big Data Technology and System Service Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology China
Temporal Graph Neural Network (TGNN) has attracted much research attention because it can capture the dynamic nature of complex networks. However, existing solutions suffer from redundant computation overhead and exce... 详细信息
来源: 评论
Soft-GNN:towards robust graph neural networks via self-adaptive data utilization
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Frontiers of Computer Science 2025年 第4期19卷 1-12页
作者: Yao WU Hong HUANG Yu SONG Hai JIN National Engineering Research Center for Big Data Technology and System Service Computing Technology and System LabCluster and Grid Computing LabSchool of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China College of Information and Communication National University of Defense TechnologyWuhan 430019China Department of Computer Science and Operations Research Universitéde MontréalMontreal H3C 3J7Canada
Graph neural networks(GNNs)have gained traction and have been applied to various graph-based data analysis tasks due to their high ***,a major concern is their robustness,particularly when faced with graph data that h... 详细信息
来源: 评论
Towards High-throughput and Low-latency Billion-scale Vector Search via CPU/GPU Collab.rative Filtering and Re-ranking  23
Towards High-throughput and Low-latency Billion-scale Vector...
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23rd USENIX Conference on File and Storage Technologies, FAST 2025
作者: Tian, Bing Liu, Haikun Tang, Yuhang Xiao, Shihai Duan, Zhuohui Liao, Xiaofei Jin, Hai Zhang, Xuecang Zhu, Junhua Zhang, Yu National Engineering Research Center for Big Data Technology and System Service Computing Technology and System Lab/Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology China Huawei Technologies Co. Ltd. China
Approximate nearest neighbor search (ANNS) has emerged as a crucial component of database and AI infrastructure. Ever-increasing vector datasets pose significant challenges in terms of performance, cost, and accuracy ... 详细信息
来源: 评论
CDA-GNN: A Chain-driven Accelerator for Efficient Asynchronous Graph Neural Network  24
CDA-GNN: A Chain-driven Accelerator for Efficient Asynchrono...
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61st ACM/IEEE Design Automation Conference, DAC 2024
作者: Yu, Hui Zhang, Yu He, Ligang He, Donghao Li, Qikun Zhao, Jin Liao, Xiaofei Jin, Hai Gu, Lin Liu, Haikun National Engineering Research Center for Big Data Technology and System Service Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology China Department of Computer Science University of Warwick United Kingdom
Asynchronous Graph Neural Network (AGNN) has attracted much research attention because it enables faster convergence speed than the synchronous GNN. However, existing software/hardware solutions suffer from redundant ... 详细信息
来源: 评论
RAHP: A Redundancy-aware Accelerator for High-performance Hypergraph Neural Network  57
RAHP: A Redundancy-aware Accelerator for High-performance Hy...
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57th Annual IEEE/ACM International Symposium on Microarchitecture, MICRO 2024
作者: Yu, Hui Zhang, Yu He, Ligang Zhao, Yingqi Li, Xintao Xin, Ruida Zhao, Jin Liao, Xiaofei Liu, Haikun He, Bingsheng Jin, Hai School of Computer Science and Technology Huazhong University of Science and Technology Natl. Eng. Res. Ctr. for Big Data Technology and System Service Computing Technology and System Lab Cluster and Grid Computing Lab Wuhan430074 China University of Warwick Department of Computer Science United Kingdom National University of Singapore Singapore
Hypergraph Neural Network (HyperGNN) has emerged as a potent methodology for dissecting intricate multilateral connections among various entities. Current software/hardware solutions leverage a sequential execution mo... 详细信息
来源: 评论
AegonKV: a high bandwidth, low tail latency, and low storage cost KV-separated LSM store with SmartSSD-based GC offloading  25
AegonKV: a high bandwidth, low tail latency, and low storage...
收藏 引用
Proceedings of the 23rd USENIX Conference on File and Storage Technologies
作者: Zhuohui Duan Hao Feng Haikun Liu Xiaofei Liao Hai Jin Bangyu Li National Engineering Research Center for Big Data Technology and System Service Computing Technology and System Lab/Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology China
The key-value separation is renowned for its significant mitigation of the write amplification inherent in traditional LSM trees. However, KV separation potentially increases performance overhead in the management of ...
来源: 评论
Graph for Science: From API based Programming to Graph Engine based Programming for HPC
arXiv
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arXiv 2023年
作者: Zhang, Yu Wang, Zixiao Zhao, Jin Guo, Yuluo Yu, Hui Huang, Zhiying Shi, Xuanhua Liao, Xiaofei National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab. Cluster and Grid Computing Lab. School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China
Modern scientific applications predominantly run on large-scale computing platforms, necessitating collab.ration between scientific domain experts and high-performance computing (HPC) experts. While domain experts are... 详细信息
来源: 评论
SumPA: Efficient Pattern-Centric Graph Mining with Pattern Abstraction  21
SumPA: Efficient Pattern-Centric Graph Mining with Pattern A...
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Proceedings of the 30th International Conference on Parallel Architectures and Compilation Techniques
作者: Chuangyi Gui Xiaofei Liao Long Zheng Pengcheng Yao Qinggang Wang Hai Jin National Engineering Research Center for Big Data Technology and System/Service Computing Technology and System Lab/Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China
Graph mining aims to explore interesting structural information of a graph. Pattern-centric systems typically transform a generic-purpose graph mining problem into a series of subgraph matching problems for high perfo... 详细信息
来源: 评论