A parallel data distribution management algorithm

Abstract

Abstract-Identifying intersections among a set of ddimensional rectangular regions (d-rectangles) is a common problem in many simulation and modeling applications. Since algorithms for computing intersections over a large number of regions can be computationally demanding, an obvious solution is to take advantage of the multiprocessing capabilities of modern multicore processors. Unfortunately, many solutions employed for the Data Distribution Management service of the High Level Architecture are either inefficient, or can only partially be parallelized. In this paper we propose the Interval Tree Matching (ITM) algorithm for computing intersections among d-rectangles. ITM is based on a simple Interval Tree data structure, and exhibits an embarrassingly parallel structure. We implement the ITM algorithm, and compare its sequential performance with two widely used solutions (brute force and sort-based matching). We also analyze the scalability of ITM on shared-memory multicore processors. The results show that the sequential implementation of ITM is competitive with sort-based matching; moreover, the parallel implementation provides good speedup on multicore processors.

Parallel sort-based matching for data distribution management on shared-memory multiprocessors

“…Only few parallel solutions for DDM and interest matching [15] have been proposed. Among them, the authors of this paper have proposed the Interval Tree Matching (ITM) algorithm for computing intersections among d-rectangles [18]. ITM is based on an interval tree data structure, and after the tree is built, exhibits an embarrassingly parallel structure.…”

“…ITM is based on an interval tree data structure, and after the tree is built, exhibits an embarrassingly parallel structure. The performance evaluation reported in [18] shows that the sequential implementation of ITM is competitive with the sequential implementation of SBM.…”

“…In this section we evaluate the performance and scalability of parallel SBM with respect to parallel versions of the BF and ITM algorithms. BF and ITM are considered because both exhibit an embarrassingly parallel structure, and ITM has already been shown to be more computationally efficient than BF [18]. In the present study we do not consider the GB algorithm: while it can be very fast and contains easily exploitable parallelism, its efficiency depends on the grid size G that should either be judiciously selected, or adaptively defined by means of non-trivial heuristics [6].…”

New advances in large‐scale distributed simulation and real‐time applications

“…As the overlap increases, new challenges appear, mostly for enabling applications, like serious gaming [10], virtual and augmented reality, and collaborative virtual environments [11], to execute seamlessly on distributed resources [12][13][14].This special issue intends to collect the state-of-the-art research works that include a set of concepts on high performance computing; design, modeling, and validation of distributed real-time systems; and multi-agent control and simulation systems. This issue also presents as objective to enable access to future trends and directions in the scope of simulations and real-time systems, covering cloud-based simulations, simulation in GPUs, and implementation of distributed virtual environment applications.…”

“…As the overlap increases, new challenges appear, mostly for enabling applications, like serious gaming [10], virtual and augmented reality, and collaborative virtual environments [11], to execute seamlessly on distributed resources [12][13][14].…”