Hyper-Real-Time Ice Simulation and Modeling Using GPGPU

Abstract

Simulation of the behaviour of a ship operating in pack ice is a computationally intensive process to which General Purpose Computing on Graphical Processing Units (GPGPU) can be applied. GPGPU is the use of a GPU (graphics processing unit) to do general purpose scientific and engineering computing. The model for GPU computing is to use a CPU and GPU together in a heterogeneous co-processing computing platform. The sequential part of the application runs on the CPU and the computationally-intensive part is accelerated by the GPU. From the users perspective, the application just runs faster because it is using the high-performance of the GPU to boost performance. This thesis presents an efficient parallel implementation of such a simulator developed using the NVIDIA Compute Unified Device Architecture (CUDA). This simulator can be used to give users the ability to analyze ice-interactions for design, assessment and training purposes. This thesis also describes the execution of experiments to evaluate the performance of the simulator and to validate the numerical modeling of ship operations in pack ice. It also describes the useful applications that have been done using this simulator in planning ice management activities. i

A review of discrete element simulation of ice–structure interaction

“…Real-time simulation of ship navigation can be useful in crew training and in planning of marine operations. For such simulations, models relying on physics engines and general-purpose computing on graphical processing units have been developed [ 16 , 18 – 21 , 31 , 118 , 119 ]. Physics engines are software systems dedicated to fast physics-related calculations such as rigid body dynamics, are used in computer games, and may prioritize speed over accuracy.…”

“…In the classical DEM formulation, the blocks are rigid, contact forces are solved by using models mimicking the effect of contact deformation, and the simulations are explicit and advance in short time steps. (Recently, implicit, non-smooth and event-driven DEM simulations have also been used [16][17][18][19][20][21], but these techniques are not described here for brevity.) On a given time step, the contact forces (figure 2) and external forces acting on each block are solved, Newton's second law is used to determine the accelerations, and a numerical integration scheme of choice is used to update the velocities and positions of each block.…”

Virtual Infrastructure Optimisation

“…combining species distribution models with weather models to study how diseases are distributed via insects and species migration at different times. Simulating physical systems does not always require the simulation to run at wall clock rates [25], but executing such simulations on distributed infrastructure does impose requirements on managing the simulation times of different sub-components, e.g. to control the relationships among events and time [26].…”

GPU-Based Monte-Carlo Simulation for a Sea Ice Load Application

“…This method constructs probability distributions of ice environmental parameters. We have applied the GPGPU approach with CUDA programming to implement this interaction model between sea ice and a vertical structure [6].…”

“…This development in GPUs computation have permitted the simulating of massive event set in timely and practical way. For instance, research has been done to demonstrate performance benefit of GPGPUs for simulating the complex mechanics of a ship operating in pack ice and it proved that GPUs have the potential to reduce the computational time significantly [6].…”