Task-based crowd simulation for heterogeneous architectures
Document typePart of book or chapter of book
Rights accessRestricted access - publisher's policy
Industry trends in the coming years imply the availability of cluster computing with hundreds to thousands of cores per chip, as well as the use of accelerators. Programming presents a challenge due to this heterogeneous architecture; thus, using novel programming models that facilitate this process is necessary. In this chapter, the case of simulation and visualization of crowds is presented. The authors analyze and compare the use of two programming models: OmpSs and CUDA. OmpSs allows to take advantage of all the resources available per node by combining the CPU and GPU while automatically taking care of memory management, scheduling, communications and synchronization. Experimental results obtained from Fermi, Kepler and Maxwell GPU architectures are presented, and the different modes used for visualizing the results are described, as well.
CitationPerez, H., Hernandez, B., Rudomin, I., Ayguade, E. Task-based crowd simulation for heterogeneous architectures. A: "Innovative research and applications in next-generation high performance computing". 2016, p. 194-219.
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