Partially observable Markov decision process (POMDP) is commonly used to model a stochastic environment with unobservable states for supporting optimal decision making. Computing ...
Improvements in the software development process depend on our ability to collect and analyze data drawn from various phases of the development life cycle. Our design metrics rese...
Both the logic and the stochastic analysis of discrete-state systems are hindered by the combinatorial growth of the state space underlying a high-level model. In this work, we con...
We present a model for the parallel performance of algorithms that consist of concurrent, two-dimensional wavefronts implemented in a message passing environment. The model combine...
Adolfy Hoisie, Olaf M. Lubeck, Harvey J. Wasserman
To prepare for future peta- or exa-scale computing, it is important to gain a good understanding on what impacts a hierarchical storage system would have on the performance of data...
Weikuan Yu, Sarp Oral, Shane Canon, Jeffrey S. Vet...