This paper examines high dimensional regression with noise-contaminated input and output data. Goals of such learning problems include optimal prediction with noiseless query poin...
Basic data flow patterns which we call idioms, such as stream, transpose, reduction, random access and stencil, are common in scientific numerical applications. We hypothesize tha...
Jiahua He, Allan Snavely, Rob F. Van der Wijngaart...
We propose a parallel and distributed component framework for building Grid applications, adapted to the hierarchical, highly distributed, highly heterogeneous nature of Grids. Thi...
As supercomputers are being built from an ever increasing number of processing elements, the effort required to achieve a substantial fraction of the system peak performance is con...
The composite signal flow model of computation targets systems with significant control and data processing parts. It builds on the data flow and synchronous data flow models ...