Traditional performance analysis techniques are performed after a parallel program has completed. In this paper, we describe an online method for continuously monitoring the perfor...
Isaac Dooley, Chee Wai Lee, Laxmikant V. Kal&eacut...
The availability of large-scale computing platforms comprised of tens of thousands of multicore processors motivates the need for the next generation of highly scalable sparse line...
Peta-scale scientific applications running on High End Computing (HEC) platforms can generate large volumes of data. For high performance storage and in order to be useful to scien...
Fang Zheng, Hasan Abbasi, Ciprian Docan, Jay F. Lo...
This brief presents an efficient and scalable online learning algorithm for recurrent neural networks (RNNs). The approach is based on the real-time recurrent learning (RTRL) algor...
— Data-centric applications are still a challenging issue for Large Scale Distributed Computing Systems. The emergence of new protocols and softwares for collaborative content di...