14275613
An empirical performance analysis of commodity memories in commodity servers
This work details a performance study of six different types of commodity memories in two commodity server nodes. A number of micro-benchmarks are used that measure low-level performance characteristics, as well as two applications representative of the ASC workload. The memories vary both in terms of performance, including latency and bandwidths, and in terms of their physical properties and manufacturer. The two server nodes analyzed were an Itanium-II Madison based system, and a Xeon based system. All memories can be used within both of these processing nodes. This allows the performance of the memories to be directly examined while keeping all other factors within a node the same (processor, motherboard, operating system etc.). The results of this study show that there can be a significant difference in application performance depending on the actual memory used - by as much as 20%. The achieved performance is a result of the integration of the memory into the node as well as how the applications actually utilize it.
53225813
Architecture - A performance comparison through benchmarking and modeling of three leading supercomputers: blue Gene/L, Red Storm, and Purple
11728820
The Hugin Tool for Probabilistic Graphical Models
As the framework of probabilistic graphical models becomes increasingly popular for knowledge representation and inference, the need for efficient tools for its support is increasing. The Hugin Tool is a general purpose tool for construction, maintenance, and deployment of Bayesian networks and influence diagrams. This paper surveys the key functionality of the Hugin Tool and reports on new advances of the tool. Furthermore, an empirical analysis reports on the efficiency of the Hugin Tool on common inference and learning tasks.
9385354
The Hugin Tool for Learning Bayesian Networks
In this paper, we describe the Hugin Tool as an efficient tool for knowledge discovery through construction of Bayesian networks by fusion of data and domain expert knowledge. The Hugin Tool supports structural learning, parameter estimation, and adaptation of parameters in Bayesian networks. The performance of the Hugin Tool is illustrated using real-world Bayesian networks, commonly used examples from the literature, and randomly generated Bayesian networks.
34671312
Hugin - The Tool for Bayesian Networks and Influence Diagrams