FlexIO: I/O middleware for location-flexible scientific data analytics

F Zheng, H Zou, G Eisenhauer… - 2013 IEEE 27th …, 2013 - ieeexplore.ieee.org
F Zheng, H Zou, G Eisenhauer, K Schwan, M Wolf, J Dayal, TA Nguyen, J Cao, H Abbasi
2013 IEEE 27th International Symposium on Parallel and Distributed …, 2013ieeexplore.ieee.org
Increasingly severe I/O bottlenecks on High-End Computing machines are prompting
scientists to process simulation output data online while simulations are running and before
storing data on disk. There are several options to place data analytics along the I/O path: on
compute nodes, on separate nodes dedicated to analytics, or after data is stored on
persistent storage. Since different placements have different impact on performance and
cost, there is a consequent need for flexibility in the location of data analytics. The FlexIO …
Increasingly severe I/O bottlenecks on High-End Computing machines are prompting scientists to process simulation output data online while simulations are running and before storing data on disk. There are several options to place data analytics along the I/O path: on compute nodes, on separate nodes dedicated to analytics, or after data is stored on persistent storage. Since different placements have different impact on performance and cost, there is a consequent need for flexibility in the location of data analytics. The FlexIO middleware described in this paper makes it easy for scientists to obtain such flexibility, by offering simple abstractions and diverse data movement methods to couple simulation with analytics. Various placement policies can be built on top of FlexIO to exploit the trade-offs in performing analytics at different levels of the I/O hierarchy. Experimental results demonstrate that FlexIO can support a variety of simulation and analytics workloads at large scale through flexible placement options, efficient data movement, and dynamic deployment of data manipulation functionalities.
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