Stream computing research is moving from terascale to petascale levels. It aims to rapidly analyze data as it streams in from many sources and make decisions with high speed and a...
Ankur Narang, Vikas Agarwal, Monu Kedia, Vijay K. ...
Learning the underlying model from distributed data is often useful for many distributed systems. In this paper, we study the problem of learning a non-parametric model from distr...
As computational clusters increase in size, their mean-time-to-failure reduces. Typically checkpointing is used to minimize the loss of computation. Most checkpointing techniques, ...
Distributed applications, especially the ones being I/O intensive, often access the storage subsystem in a non-sequential way (stride requests). Since such behaviors lower the ove...
—In addition to their role as simulation engines, modern supercomputers can be harnessed for scientific visualization. Their extensive concurrency, parallel storage systems, and...
Tom Peterka, Hongfeng Yu, Robert B. Ross, Kwan-Liu...