발간년도 : [2021]
| 논문정보 |
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| 논문명(한글) |
[Vol.16, No.3] Optimizing NUMA System Beyond 100 Gbps for Big Data |
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| 논문투고자 |
Se-young Yu |
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| 논문내용 |
As big data science and analysis become prevalent in the science community and industry, systems to store, access, and share big data are studied in many ways. As compute resources to execute big data analysis move to the cloud, the storage system integrates to the cloud to provide storage services to the compute resources. The accessibility of big data is important to cloud computing because the analysis jobs that run in the cloud often migrate to another compute node. The storage service needs to provide the resource to multiple compute nodes with NUMA support. Current High-performance data management systems focus on the accessibility of storage systems and lack of performance optimization for transferring data in NUMA system. Big data and cloud computing's popularity enhance the trend of universally accessible data, yet accessing remote data is limited significantly due to the lack of optimization on the data path within the systems and the networks. Our systematic approach to optimize a NUMA system provides fully utilizing end-to-end data transfer streams with 100 Gbps disk-to-disk throughput. We use our model to show we can utilize the 100 Gbps network with disk-to-disk transfer using commodity hardware and open-source tools with optimizing NUMA system. |
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