Current visualization tools lack the ability to perform fullrange spatial and temporal analysis on terascale scientific datasets. Two key reasons exist for this shortcoming: I/O ...
Wesley Kendall, Markus Glatter, Jian Huang, Tom Pe...
The scalability of future massively parallel processing (MPP) systems is being severely challenged by high failure rates. Current hard disk drive (HDD) checkpointing results in ov...
Xiangyu Dong, Naveen Muralimanohar, Norman P. Joup...
Reconfigurable computing (RC) systems based on FPGAs are becoming an increasingly attractive solution to building parallel systems of the future. Applications targeting such syste...
Vikas Aggarwal, Alan D. George, K. Yalamanchili, C...
A stock market data processing system that can handle high data volumes at low latencies is critical to market makers. Such systems play a critical role in algorithmic trading, ri...
Xiaolan J. Zhang, Henrique Andrade, Bugra Gedik, R...
Energy minimization is an important step in molecular modeling, with applications in molecular docking and in mapping binding sites. Minimization involves repeated evaluation of v...
In this paper we propose a new provenance model which is tailored to a class of workflow-based applications. We motivate the approach with use cases from the astronomy community. ...
Paul T. Groth, Ewa Deelman, Gideon Juve, Gaurang M...
MapReduce provides a parallel and scalable programming model for data-intensive business and scientific applications. MapReduce and its de facto open source project, called Hadoop...
The availability of large quantities of processors is a crucial enabler of many-task computing. Voluntary computing systems have proven that it is possible to build computing plat...
Rostand Costa, Francisco V. Brasileiro, Guido Lemo...
Error Subspace Statistical Estimation (ESSE), an uncertainty prediction and data assimilation methodology employed for real-time ocean forecasts, is based on a characterization an...
Constantinos Evangelinos, Pierre F. J. Lermusiaux,...