Development of a convex polyhedral discrete element simulation framework for NVIDIA Kepler based GPUs
نویسندگان
چکیده
Understanding the dynamical behavior of Granular Media (GM) is extremely important to many industrial processes. Thus simulating the dynamics of GM is critical in the design and optimization of such processes. However, the dynamics of GM is complex in nature and cannot be described by a closed form solution for more than a few particles. A popular and successful approach in simulating the underlying dynamics of GM is by using the Discrete Element Method (DEM). Computational viable simulations are typically restricted to a few particles with realistic complex interactions or a larger number of particles with simplified interactions. This paper introduces a novel DEM based particle simulation code (BLAZE-DEM) that is capable of simulating millions of particles on a desktop computer utilizing a NVIDIA Kepler Graphical Processor Unit (GPU) via the CUDA programming model. The GPU framework of BLAZE-DEM is limited to applications that require large numbers of particles with simplified interactions such as hopper flow which exhibits task level parallelism that can be exploited on the GPU. BLAZE-DEM also performs real-time visualization with interactive capabilities. In this paper we discuss our GPU framework and validate our code by comparison between experimental and numerical hopper flow.
منابع مشابه
Collision detection of convex polyhedra on the NVIDIA GPU architecture for the discrete element method
Convex polyhedra represent granular media well. This geometric representation may be critical in obtaining realistic simulations of many industrial processes using the discrete element method (DEM). However detecting collisions between the polyhedra and surfaces that make up the environment and the polyhedra themselves is computationally expensive. This paper demonstrates the significant comput...
متن کاملConjugate gradient solvers on Intel Xeon Phi and NVIDIA GPUs
Lattice Quantum Chromodynamics simulations typically spend most of the runtime in inversions of the Fermion Matrix. This part is therefore frequently optimized for various HPC architectures. Here we compare the performance of the Intel R Xeon Phi TM to current Kepler-based NVIDIA R Tesla TM GPUs running a conjugate gradient solver. By exposing more parallelism to the accelerator through inverti...
متن کاملHISQ inverter on Intel Xeon Phi and NVIDIA GPUs
The runtime of a Lattice QCD simulation is dominated by a small kernel, which calculates the product of a vector by a sparse matrix known as the “Dslash” operator. Therefore, this kernel is frequently optimized for various HPC architectures. In this contribution we compare the performance of the Intel R © Xeon Phi TM to current Kepler-based NVIDIA R © Tesla TM GPUs running a conjugate gradient ...
متن کاملPerformance of Kepler GTX Titan GPUs and Xeon Phi System
NVIDIA’s new architecture, Kepler improves GPU’s performance significantly with the new streaming multiprocessor SMX. Along with the performance, NVIDIA has also introduced many new technologies such as direct parallelism, hyper-Q and GPU Direct with RDMA. Apart from other usual GPUs, NVIDIA also released another Kepler ‘GeForce’ GPU named GTX Titan. GeForce GTX Titan is not only good for gamin...
متن کاملOptimizing Stencil Computations for NVIDIA Kepler GPUs
We present a series of optimization techniques for stencil computations on NVIDIA Kepler GPUs. Stencil computations with regular grids had been ported to the older generations of NVIDIA GPUs with significant performance improvements thanks to the higher memory bandwidth than conventional CPU-only systems. However, because of the architectural changes introduced with the latest generation of the...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- J. Computational Applied Mathematics
دوره 270 شماره
صفحات -
تاریخ انتشار 2014