Real-time collision culling of a million bodies on graphics processing units

Liu, Fuchang; Harada, Takahiro; Lee, Young‐Eun; Kim, Young Jin

doi:10.1145/1882262.1866180

Cited by 15 publications

(26 citation statements)

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“…Several authors present comparative studies to validate their novel algorithm's efficiency. Broadly, these works can be divided on whether synthetic data [LLCC13, TBW09, CL16a, CL18] or physical simulations [LCF05, SR17, LHLK10, TB12, WM09] have been used to perform collision detection tests. Studies using synthetic data generally consist of constant‐speed objects that bounce on the scene walls.…”

Section: Related Workmentioning

confidence: 99%

“…With regard to analysis, the majority of existing works focus on scalability and include analysis of some other properties relevant to the developed approach. Algorithms that make use of temporal techniques commonly analyse performance across the number of moving objects [LHLK10, SR17, TB12, CL18], showing their speedups on predictable scenes. Works based on Grid‐like spatial subdivisions usually present some form of non‐uniformly distributed objects analysis [LLCC13, AGA12].…”

Section: Related Workmentioning

confidence: 99%

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Broadmark: A Testing Framework for Broad‐Phase Collision Detection Algorithms

Serpa

Rodriguês

2019

Computer Graphics Forum

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Research in the area of collision detection permeates most of the literature on simulations, interaction and agents planning, being commonly regarded as one of the main bottlenecks for large‐scale systems. To this day, despite its importance, most subareas of collision detection lack a common ground to test and validate solutions, reference implementations and widely accepted benchmark suites. In this paper, we delve into the broad‐phase of collision detection systems, providing both an open‐source framework, named Broadmark, to test, compare and validate algorithms, and an in‐deep analysis of the main techniques used so far to tackle the broad‐phase problem. The technical challenges of building this framework from the software and hardware perspectives are also described. Within our framework, several original and state‐of‐the‐art implementations of CPU and GPU algorithms are bundled, alongside three benchmark scenes to stress algorithms under several conditions. Furthermore, the system is designed to be easily extensible. We use our framework to bring out an extensive performance comparison among assembled solutions, detailing the current CPU and GPU state‐of‐the‐art on a common ground. We believe that Broadmark encompasses the principal insights and tools to derive and evaluate novel algorithms, thus greatly facilitating discussion about successful broad‐phase collision detection solutions.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Broadmark: A Testing Framework for Broad‐Phase Collision Detection Algorithms

Serpa

Rodriguês

2019

Computer Graphics Forum

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“…Complementary to our approach, collision detection for fracture simulations can also benefit in several ways from fast parallel algorithms executed on graphics processors: for fast culling in piles of objects [28], collision detection queries with no need for preprocessing [29], or fast computation of data structures, either distance fields [9] or bounding volume hierarchies [30]. We have designed methods that achieve high performance by reducing computations (i.e., they are less computationally demanding than previous methods), and could also benefit from parallel implementations.…”

Section: Related Workmentioning

confidence: 99%

Fast Collision Detection for Fracturing Rigid Bodies

Glondu

Schvartzman

Marchal

et al. 2014

IEEE Trans. Visual. Comput. Graphics

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In complex scenes with many objects, collision detection plays a key role in the simulation performance. This is particularly true in fracture simulation for two main reasons. One is that fracture fragments tend to exhibit very intensive contact, and the other is that collision detection data structures for new fragments need to be computed on the fly. In this paper, we present novel collision detection algorithms and data structures for real-time simulation of fracturing rigid bodies. We build on a combination of well-known efficient data structures, namely, distance fields and sphere trees, making our algorithm easy to integrate on existing simulation engines. We propose novel methods to construct these data structures, such that they can be efficiently updated upon fracture events and integrated in a simple yet effective self-adapting contact selection algorithm. Altogether, we drastically reduce the cost of both collision detection and collision response. We have evaluated our global solution for collision detection on challenging scenarios, achieving high frame rates suited for hard real-time applications such as video games or haptics. Our solution opens promising perspectives for complex fracture simulations involving many dynamically created rigid objects.

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“…Using physical simulation , some methods are capable of generating aggregates that consist of a large number of objects [MSJT08, LHLK10]. In addition, various methods have been proposed for easily generating the desired piles by using a guide that specifies the shape of an aggregate [HK12, HK10, Cho07].…”

Section: Related Workmentioning

confidence: 99%

Modelling of Non‐Periodic Aggregates Having a Pile Structure

Sakurai

Miyata

2013

Computer Graphics Forum

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This paper presents a procedure for modelling aggregates such as piles that consist of arbitrary components. The method generates an aggregate of components that need to be accumulated, and an aggregate shape represents the surface of the target aggregate. The number of components and their positions and orientations are controlled by five parameters. The components, the aggregate shape and the parameters are the inputs for the method which involves placement and refinement steps. In the placement step, the orientation and initial position of a component are determined by a non-periodic placement such that each component overlaps its neighbours. In the refinement step, to construct a pile structure, the position of each component is adjusted by reducing the overlap.

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Real-time collision culling of a million bodies on graphics processing units

Cited by 15 publications

References 0 publications

Broadmark: A Testing Framework for Broad‐Phase Collision Detection Algorithms

Broadmark: A Testing Framework for Broad‐Phase Collision Detection Algorithms

Fast Collision Detection for Fracturing Rigid Bodies

Modelling of Non‐Periodic Aggregates Having a Pile Structure

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