A common approach for dealing with large data sets is to stream over the input in one pass, and perform computations using sublinear resources. For truly massive data sets, howeve...
Jon Feldman, S. Muthukrishnan, Anastasios Sidiropo...
To make efficient use of CMPs with tens to hundreds of cores, it is often necessary to exploit fine-grain parallelism. However, managing tasks of a few thousand instructions is ...
Daniel Sanchez, Richard M. Yoo, Christos Kozyrakis
Abstract. The resolution of combinatorial optimization problems can greatly benefit from the parallel and distributed processing which is characteristic of neural network paradigm...
We present a novel design and implementation of relational join algorithms for new-generation graphics processing units (GPUs). The most recent GPU features include support for wr...
Bingsheng He, Ke Yang, Rui Fang, Mian Lu, Naga K. ...
A problem with running distributed shared memory applications in heterogeneous environments is that making optimal use of available resources often requires significant changes t...