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Scientific codes are all subject to variation in performance depending on the runtime platform and/or configuration, the output writing API employed, and the file system for output. Since changing the IO routines to match the optimal or desired configuration for a given system can be costly in terms of human time and machine resources, the Adaptable IO(More)
  • William F Laurance, D Carolina Useche, Julio Rendeiro, Margareta Kalka, Corey J A Bradshaw, Sean P Sloan +210 others
  • 2012
The rapid disruption of tropical forests probably imperils global biodiversity more than any other contemporary phenomenon. With deforestation advancing quickly, protected areas are increasingly becoming final refuges for threatened species and natural ecosystem processes. However, many protected areas in the tropics are themselves vulnerable to human(More)
Hierarchical clustering has been widely used in numerous applications due to its informative representation of clustering results. But its higher computation cost and inherent data dependency prohibits it from performing on large datasets efficiently. In this paper, we present a distributed single-linkage hierarchical clustering algorithm (DiSC) based on(More)
In collective I/O, MPI processes exchange requests so that the rearranged requests can result in the shortest file system access time. Scheduling the exchange sequence determines the response time of participating processes. Existing implementations that simply follow the increasing order of file offsets do not necessary produce the best performance. To(More)
ADIOS is a state of the art componentization of the IO system that has demonstrated impressive IO performance results on the Cray XT system at ORNL. ADIOS separates the selection and implementation of any particular IO routines from the scientific code offering unprecedented flexibility in the choices for processing and storing data. The API was modelled on(More)
Several important combinatorial optimization problems can be formulated as maximum a posteriori (MAP) inference in discrete graphical models. We adopt the recently proposed parallel MAP inference algorithm Bethe-ADMM and implement it using message passing interface (MPI) to fully utilize the computing power provided by the modern supercomputers with(More)
—Recommender systems are vital to the success of online retailers and content providers. One particular challenge in recommender systems is the " cold start " problem. The word " cold " refers to the items that are not yet rated by any user or the users who have not yet rated any items. We propose ELVER to recommend and optimize page-interest targeting on(More)
AIM To optimize formulation methods for loading gemcitabine (GEM), the main drug against pancreatic cancer, into albumin nanoparticles for extended blood circulation and improved efficacy. METHODS GEM was loaded into two sizes of disolvation-crosslinked bovine serum albumin nanoparticles, with a mean diameter of 109.7 nm and 405.6 nm, respectively, by(More)
— An important problem in discrete graphical models is the maximum a posteriori (MAP) inference problem. Recent research has been focusing on the development of parallel MAP inference algorithm, which scales to graphical models of millions of nodes. In this paper, we introduce a parallel implementation of the recently proposed Bethe-ADMM algorithm using(More)