Scientists have long relied on abstract models to study phenomena that are too complex for direct observation and experimentation. As new scientific modeling methodologies emerge...
High performance data grids are increasingly becoming popular platforms to support data-intensive applications. Reducing high energy consumption caused by data grids is a challeng...
We present tools that support the runtime execution of applications that mix software running on networks of workstations and reconfigurable hardware. We use JHDL to describe the ...
Laurie A. Smith King, Heather Quinn, Miriam Leeser...
As grid computation systems become larger and more complex, manually diagnosing failures in jobs becomes impractical. Recently, machine-learning techniques have been proposed to d...
The goal of the work described in this paper is to design and build a scalable infrastructure for executing grid applications on a widely distributed set of resources. Such grid i...
Jik-Soo Kim, Beomseok Nam, Michael A. Marsh, Peter...