Spatial partitioning of geometry images using locality masks

2005 ◽  
Author(s):  
L. Domanski ◽  
M. Cook
Keyword(s):  
Spatial Partitioning

Methods to Accelerate Ray Tracing in the Monte Carlo Method for Surface-to-Surface Radiation Transport

2006 ◽  
Vol 128 (9) ◽  
pp. 945-952 ◽  
Author(s):  
Sandip Mazumder
Keyword(s):  
Monte Carlo ◽  
Ray Tracing ◽  
Radiation Transport ◽  
Three Dimensional ◽  
Intersection Point ◽  
Surface Radiation ◽  
Computational Domain ◽  
Two Dimensional ◽  
Spatial Partitioning ◽  
The Monte Carlo Method

Two different algorithms to accelerate ray tracing in surface-to-surface radiation Monte Carlo calculations are investigated. The first algorithm is the well-known binary spatial partitioning (BSP) algorithm, which recursively bisects the computational domain into a set of hierarchically linked boxes that are then made use of to narrow down the number of ray-surface intersection calculations. The second algorithm is the volume-by-volume advancement (VVA) algorithm. This algorithm is new and employs the volumetric mesh to advance the ray through the computational domain until a legitimate intersection point is found. The algorithms are tested for two classical problems, namely an open box, and a box in a box, in both two-dimensional (2D) and three-dimensional (3D) geometries with various mesh sizes. Both algorithms are found to result in orders of magnitude gains in computational efficiency over direct calculations that do not employ any acceleration strategy. For three-dimensional geometries, the VVA algorithm is found to be clearly superior to BSP, particularly for cases with obstructions within the computational domain. For two-dimensional geometries, the VVA algorithm is found to be superior to the BSP algorithm only when obstructions are present and are densely packed.

scholarly journals JAX, M.D. A framework for differentiable physics*

2021 ◽  
Vol 2021 (12) ◽  
pp. 124016
Author(s):  
Samuel S Schoenholz ◽  
Ekin D Cubuk
Keyword(s):  
Neural Networks ◽  
Molecular Dynamics ◽  
Scale Up ◽  
Spatial Partitioning ◽  
Differentiable Functions ◽  
Physics Simulation ◽  
Multi Agent ◽  
Graph Neural Networks ◽  
Meta Optimization ◽  
Particle Packings

Abstract We introduce JAX MD, a software package for performing differentiable physics simulations with a focus on molecular dynamics. JAX MD includes a number of physics simulation environments, as well as interaction potentials and neural networks that can be integrated into these environments without writing any additional code. Since the simulations themselves are differentiable functions, entire trajectories can be differentiated to perform meta-optimization. These features are built on primitive operations, such as spatial partitioning, that allow simulations to scale to hundreds-of-thousands of particles on a single GPU. These primitives are flexible enough that they can be used to scale up workloads outside of molecular dynamics. We present several examples that highlight the features of JAX MD including: integration of graph neural networks into traditional simulations, meta-optimization through minimization of particle packings, and a multi-agent flocking simulation. JAX MD is available at https://www.github.com/google/jax-md.

scholarly journals Patterns of space use in sympatric marine colonial predators reveal scales of spatial partitioning

2015 ◽  
Vol 534 ◽  
pp. 235-249 ◽  
Author(s):  
EL Jones ◽  
BJ McConnell ◽  
S Smout ◽  
PS Hammond ◽  
CD Duck ◽  
...  
Keyword(s):  
Space Use ◽  
Spatial Partitioning

scholarly journals Spatial partitioning improves the reliability of biochemical signaling

2013 ◽  
Vol 110 (15) ◽  
pp. 5927-5932 ◽  
Author(s):  
A. Mugler ◽  
F. Tostevin ◽  
P. R. ten Wolde
Keyword(s):  
Spatial Partitioning

Pollination of the Rain-Forest Tree Syzygium Tierneyanum (Myrtaceae) at Kuranda, Northern Queensland

1980 ◽  
Vol 28 (2) ◽  
pp. 223 ◽  
Author(s):  
SD Hopper
Keyword(s):  
Rain Forest ◽  
Foraging Behaviour ◽  
Fruit Fly ◽  
Forest Tree ◽  
The Self ◽  
Spatial Partitioning ◽  
Mass Flowering ◽  
Foraging Modes ◽  
Flowering Branch ◽  
Floral Visitors

The identity, abundance and foraging behaviour of pollinators of the self-compatible, mass-flowering Syzygium tierneyanum were investigated. Forty-five species of nectarivorous animals were recorded. Diurnal visitors included seven bird; nine butterfly. four moth (including two hawkmoth), two bee, two ant, one wasp, three blowfly, one fruit fly, two beetle and one weevil species. while nocturnal visitors included one bat and 12 moth (including three hawkmoth) species. Floral dimensions were such that only the vertebrate and larger insect species regularly contacted anthers and stigmas while foraging. Of these groups the feral honey bee (Apis mellifera) was the most common flowet visitor. Honeyeaters and hawkmoths appeared to be the most important native pollinators; they were abundant in the study area and visited numerous flowers (50-250) in quick succession (1-3 s per flower) on each foraging bout. The only major differences in foraging times observed in the pollinator array were between diurnal, diurnal and crepuscular, and nocturnal floral visitors. Spatial partitioning of the nectar resource was limited to one instance of territoriality involving a Macleay's honeyeater (Meliphaga rnacleayana) on a densely flowering branch prior to peak blooming time, occasional aggressive chases by honeyeaters, and a division of foraging modes into rapid, erratic flights of 0.5– 4 m between flowers (hawkmoths) as against nearest-flower movements (all other groups). This lack of major spatial partitioning may have been due to the mass flowering of S. tierneyanum and the resultant superabundance of nectar. The vast majority (c. 99.95%) of interflower movements observed in foraging bouts of birds (and of hawkmoths) were within the same plant. This suggests that most seeds of S. tierneyanum may be derived from self-pollination.

Collision Detection in Video Games

2012 ◽  
pp. 221-252
Author(s):  
Benjamin Rodrigue
Keyword(s):  
Video Games ◽  
Video Game ◽  
Collision Detection ◽  
Graphical Representation ◽  
Spatial Partitioning ◽  
Bounding Volumes ◽  
The Third ◽  
3D Environment ◽  
Bounding Boxes ◽  
Oriented Bounding Boxes

This chapter will describe several methods of detecting collision events within a 3D environment. It will also discuss some of the bounding volumes, and their intersection tests that can be used to contain the graphical representation of objects in a video game. The first part of the chapter will cover the use of Axially Aligned Bounding Boxes (AABBs) and Radial Collision Volumes. The use of hierarchies with bounding volumes will be discussed. The next section of the chapter will focus on Object Oriented Bounding Boxes (OOBs). The third section is concerned with the Gilbert-Johnson-Keerthi distance algorithm (GJK). The last three sections will focus on ways of optimizing the collision detection process by culling unnecessary intersection tests through the use of type lists, sorted lists and spatial partitioning.

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