Traditional architectural designs are normally focused on CPUs and have been often decoupled from I/O considerations. They are inefficient for high-speed network processing with a...
We describe a new suite of computational benchmarks that models applications featuring multiple levels of parallelism. Such parallelism is often available in realistic flow comput...
: Performance modeling for scientific production codes is of interest both for program tuning and for the selection of new machines. An empirical method is used for developing a m...
—This paper compares parallel and distributed implementations of an iterative, Gibbs sampling, machine learning algorithm. Distributed implementations run under Hadoop on facilit...
Sebastien Bratieres, Jurgen Van Gael, Andreas Vlac...
Manual parallelization of programs is known to be difficult and error-prone, and there are currently few ways to measure the amount of potential parallelism in the original sequent...