A Parallel Block Iterative Method for Interactive Contacting Rigid Multibody Simulations on Multicore PCs

Fast solution methods for complementarity problems (CPs) with several hundred variables are essential for interactive realtime simulation of systems of constrained, contacting rigid bodies. These simulations are commercially relevant for several applications such as virtual environment (VE) heavy machinery operator training systems. We describe a hybrid, asynchronous, block parallel method to approximately solve these CPs in realtime on multicore CPUs. A graph analysis phase identifies components which are weakly coupled using a physically inspired weight function. Each component is then solved in parallel using either a block principal pivot method or a projected block Gauss Seidel method running in separate threads. Couplings which generate forces between the subsystems are handled iteratively using a Gauss-Seidel process which communicates updates between the interacting subsystems asynchronously. Preliminary results show that this approach delivers good performance while keeping overhead small

Technology 2001: The Second National Technology Transfer Conference and Exposition, volume 1

Papers from the technical sessions of the Technology 2001 Conference and Exposition are presented. The technical sessions featured discussions of advanced manufacturing, artificial intelligence, biotechnology, computer graphics and simulation, communications, data and information management, electronics, electro-optics, environmental technology, life sciences, materials science, medical advances, robotics, software engineering, and test and measurement

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp