157 research outputs found
A Distributed System for Parallel Simulations
We presented the technologies and algorithms to build a web-based visualization and steering system to monitor the dynamics of remote parallel simulations executed on a Linux Cluster. The polynomial time based algorithm to optimally utilize distributed computing resources over a network to achieve maximum frame-rate was also proposed. Keeping up with the advancements in modern web technologies, we have developed an Ajax-based web frontend which allows users to remotely access and control ongoing computations via a web browser facilitated by visual feedbacks in real-time. Experimental results are also given from sample runs mapped to distributed computing nodes and initiated by users at different geographical locations. Our preliminary results on frame-rates illustrated that system performance was affected by network conditions of the chosen mapping loop including available network bandwidth and computing capacities. The underlying programming framework of our system supports mixed-programming mode and is flexible to integrate most serial or parallel simulation code written in different programming languages such as Fortran, C and Java
PPF - A Parallel Particle Filtering Library
We present the parallel particle filtering (PPF) software library, which
enables hybrid shared-memory/distributed-memory parallelization of particle
filtering (PF) algorithms combining the Message Passing Interface (MPI) with
multithreading for multi-level parallelism. The library is implemented in Java
and relies on OpenMPI's Java bindings for inter-process communication. It
includes dynamic load balancing, multi-thread balancing, and several
algorithmic improvements for PF, such as input-space domain decomposition. The
PPF library hides the difficulties of efficient parallel programming of PF
algorithms and provides application developers with the necessary tools for
parallel implementation of PF methods. We demonstrate the capabilities of the
PPF library using two distributed PF algorithms in two scenarios with different
numbers of particles. The PPF library runs a 38 million particle problem,
corresponding to more than 1.86 GB of particle data, on 192 cores with 67%
parallel efficiency. To the best of our knowledge, the PPF library is the first
open-source software that offers a parallel framework for PF applications.Comment: 8 pages, 8 figures; will appear in the proceedings of the IET Data
Fusion & Target Tracking Conference 201
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