Abstract. Exploiting the full computational power of current hierarchical multiprocessor machines requires a very careful distribution of threads and data among the underlying non-...
Learning dynamic Bayesian network structures provides a principled mechanism for identifying conditional dependencies in time-series data. An important assumption of traditional D...
Here we present a scalable method to compute the structure of causal links over large scale dynamical systems that achieves high efficiency in discovering actual functional connec...
Guillermo A. Cecchi, Rahul Garg, A. Ravishankar Ra...
This paper presents the design and experimental evaluation of two dynamic load partitioning and balancing strategies for parallel Structured Adaptive Mesh Refinement (SAMR) applic...
Abstract. We study a number of embedded DSLs for autonomous ordinary differential equations (autonomous ODEs) in Haskell. A naive implementation based on the lazy tower of derivat...