AnalyzeThis: An Analysis Workflow-Aware Storage System

Conference · Thu Jan 01 00:00:00 EST 2015

OSTI ID:1265619

Sim, Hyogi ^[1]; Kim, Youngjae ^[1]; Vazhkudai, Sudharshan S ^[1]; Tiwari, Devesh ^[1]; Anwar, Ali ^[2]; Butt, Ali R ^[2]; Ramakrishnan, Lavanya ^[3]

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1. ORNL
2. Virginia Tech, Blacksburg, VA
3. Lawrence Berkeley National Laboratory (LBNL)

The need for novel data analysis is urgent in the face of a data deluge from modern applications. Traditional approaches to data analysis incur significant data movement costs, moving data back and forth between the storage system and the processor. Emerging Active Flash devices enable processing on the flash, where the data already resides. An array of such Active Flash devices allows us to revisit how analysis workflows interact with storage systems. By seamlessly blending together the flash storage and data analysis, we create an analysis workflow-aware storage system, AnalyzeThis. Our guiding principle is that analysis-awareness be deeply ingrained in each and every layer of the storage, elevating data analyses as first-class citizens, and transforming AnalyzeThis into a potent analytics-aware appliance. We implement the AnalyzeThis storage system atop an emulation platform of the Active Flash array. Our results indicate that AnalyzeThis is viable, expediting workflow execution and minimizing data movement.

• Research Organization: Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF)
• Sponsoring Organization: USDOE Office of Science (SC)
• DOE Contract Number: AC05-00OR22725
• OSTI ID: 1265619
• Resource Relation: Conference: 2015 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis (SC'15), Austin, TX, USA, 20151115, 20151120
• Country of Publication: United States
• Language: English

Related Subjects

Data Analytics
Visualization & Storage