@conference{DataTap2,
	author = "Hasan Abbasi and Jay Lofstead and Fang Zheng and Scott Klasky and Karsten Schwan and Matthew Wolf",
	title = "Extending I/O Through High Performance Data Services",
abstract = {The complexity of HPC systems has increased the burden on the developer as applications scale to hundreds of thousands of processing cores. I/O processing is one area where extensive efforts are required to achieve acceptable performance and scalability. 

A successful approach to high performance I/O demonstrated by our group and others is to use select nodes for data staging, where data is evacuated from compute to staging nodes before being moved to the disk via the file system. This paper shows that I/O performance can be improved substantially by carefully managing how data staging is performed, and by enriching such I/O actions through additional "data services", lightweight abstractions for carrying out data processing such as transformation, reduction and scheduled storage. We evaluate data services on actual application codes within our data staging framework for asynchronous data movement, and we also describe the impact of resource management in synchronous environments. 
},
	booktitle = "Cluster Computing",
	year = "2007",
	publisher = "IEEE International",
	address = "Austin, TX",
	month = "September"
}