Boosting Graph Analytics by Tuning Threads and Data Affinity on NUMA Systems

Author:

Rocha Hiago Mayk G. de A.,Schwarzrock Janaina,Lorenzon Arthur F.,Beck Antonio Carlos S.

Publisher

IEEE

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Allok: a machine learning approach for efficient graph execution on CPU–GPU clusters;The Journal of Supercomputing;2024-05-23

2. A NUMA-aware Graph Database for Hybrid Memory System;2023 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom);2023-12-21

3. Optimizing Single-Source Graph Execution on NUMA Machines;2023 XIII Brazilian Symposium on Computing Systems Engineering (SBESC);2023-11-21

4. Using evolutionary metaheuristics to solve the mapping and routing problem in networks on chip;Design Automation for Embedded Systems;2023-03-10

5. Automatic CPU-GPU Allocation for Graph Execution;2023 31st Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP);2023-03

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