Abstract not found

Dryad is a general-purpose distributed execution engine for coarse-grain data-parallel applications. A Dryad applica-tion combines computational “vertices ” with communica-tion “channels ” to form a dataflow graph. Dryad runs the application by executing the vertices of this graph on a set of available computers, communicating as appropriate through files, TCP pipes, and shared-memory FIFOs. The vertices provided by the application developer are quite simple and are usually written as sequential programs with no thread creation or locking. Concurrency arises from Dryad scheduling vertices to run simultaneously on multi-ple computers, or on multiple CPU cores within a computer. The application can discover the size and placement of data at run time, and modify the graph as the computation pro-gresses to make efficient use of the available resources. Dryad is designed to scale from powerful multi-core sin-gle computers, through small clusters of computers, to data centers with thousands of computers. The Dryad execution engine handles all the difficult problems of creating a large distributed, concurrent application: scheduling the use of computers and their CPUs, recovering from communication or computer failures, and transporting data between ver-tices.

The building-block hypothesis states that the GA works well when short, low-order, highly-fit schemas recombine to form even more highly fit higher-order schemas. The ability to produce fitter and fitter partial solutions by combining building blocks is believed to be a primary source of the GA

EGFR-type receptor tyrosine kinases achieve a broad spectrum of cellular responses by utilizing a set of structurally conserved building blocks. Based on available crystal structures and biochemical information, significant new insights have emerged into modes of receptor control, its deregulation

. These goals and challenges are resolved into a set of functional "building blocks " that address different aspects of NORM protocol operation. It is anticipated that

he assembly of molecular building blocks with metal ions genera-ting microporous network solids has been the focus of intense activity1–12. Because of their potential applications associated with channels and cavities, such materials have been examined for size- and shape-selective catalysis

Free-space-optical mobile ad hoc networks: Auto-configurable

This and other publications and products of the National Institute of Justice can be found at:

In the light of a recently derived evolution equation for genetic algorithms we consider the schema theorem and the building block hypothesis. We derive a schema theorem based on the concept of effective fitness showing that schemata of higher than average effective fitness receive an exponentially

. The Building-Block Hypothesis appeals to the notion of problem decomposition and the assembly of solutions from sub-solutions. Accordingly, there have been many varieties of GA test problems with a structure based on buildingblocks. Many of these problems use deceptive fitness functions to model