Distributed processing of real-world graphs is challenging due to their size and the inherent irregular structure of graph computations. We present HIPG, a distributed framework th...
Elzbieta Krepska, Thilo Kielmann, Wan Fokkink, Hen...
Support Vector Machines (SVMs) suffer from a widely recognized scalability problem in both memory use and computational time. To improve scalability, we have developed a parallel ...
Edward Y. Chang, Kaihua Zhu, Hao Wang, Hongjie Bai...
We present a parallel algorithm for performing multipoint linkage analysis of genetic marker data on large family pedigrees. The algorithm effectively distributes both the computa...
Gavin C. Conant, Steve Plimpton, William Old, Andr...
This paper describes the process used to extend the Boost Graph Library (BGL) for parallel operation with distributed memory. The BGL consists of a rich set of generic graph algor...
Data parallel programs are sensitive to the distribution of data across processor nodes. We formulate the reduction of inter-node communication as an optimization on a colored gra...