JiTTree: A Just-in-Time Compiled Sparse GPU Volume Data Structure

Labschutz, Matthias; Brückner, Stefan; Gröller, M. Eduard; Hadwiger, Markus; Rautek, Peter

doi:10.1109/tvcg.2015.2467331

Cited by 15 publications

(7 citation statements)

References 26 publications

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“…The original program code (the one that is to be simulated, or executed by a virtual machine) is compiled to machine code, i.e., the code that is natively understood by the underlying machine. This compilation often happens just-in-time, i.e., while the program is running, just before the execution of the individual pieces of code [42,44]. Such technology is regularly used in most contemporary web browsers and in some programming languages and while it is neutral (undetectable) from the perspective of a running program, it causes the program to run orders of magnitude faster.…”

Section: Universes Simulated and Universes Created By Humans Todaymentioning

confidence: 99%

Universes and simulations: Civilizational development in nested embedding

Komosiński

2018

Foundations of Computing and Decision Sciences

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The rapid development of technology has allowed computer simulations to become routinely used in an increasing number of fields of science. These simulations become more and more realistic, and their energetic efficiency grows due to progress in computer hardware and software. As humans merge with machines via implants, brain-computer interfaces and increased activity involving information instead of material objects, philosophical concepts and theoretical considerations on the nature of reality are beginning to concern practical, working models and testable virtual environments. This article discusses how simulation is understood and employed in computer science today, how software, hardware and the physical universe unify, how simulated realities are embedded one in another, how complicated it can get in application, practical scenarios, and the possible consequences of these situations. A number of basic properties of universes and simulations in such multiply nested structures are reviewed, and the relationship of these properties with a level of civilizational development is explored.

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Section: Universes Simulated and Universes Created By Humans Todaymentioning

confidence: 99%

Universes and simulations: Civilizational development in nested embedding

Komosiński

2018

Foundations of Computing and Decision Sciences

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“…al. [8] who mix the two approaches into a novel data structure referred to as Jittree and fully managed by the GPU.…”

Section: Related Workmentioning

confidence: 99%

SkiMap: An efficient mapping framework for robot navigation

Gregorio

Stefano

2017

2017 IEEE International Conference on Robotics and Automation (ICRA)

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Abstract-We present a novel mapping framework for robot navigation which features a multi-level querying system capable to obtain rapidly representations as diverse as a 3D voxel grid, a 2.5D height map and a 2D occupancy grid. These are inherently embedded into a memory and time efficient core data structure organized as a Tree of SkipLists. Compared to the wellknown Octree representation, our approach exhibits a better time efficiency, thanks to its simple and highly parallelizable computational structure, and a similar memory footprint when mapping large workspaces. Peculiarly within the realm of mapping for robot navigation, our framework supports realtime erosion and re-integration of measurements upon reception of optimized poses from the sensor tracker, so as to improve continuously the accuracy of the map.

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“…Crassin et al [4] present a fast implementation of N 3 trees that is used for voxel-based ray casting of interfaces in large scenes. Labschüetz et al [13] present JiTTree, a hybrid data structure that subdivides the input domain into regular bricks. For each brick, the memory-optimal data structure is computed.…”

Section: Related Workmentioning

confidence: 99%

A Versatile and Efficient GPU Data Structure for Spatial Indexing

Schneider

Rautek

2017

IEEE Trans. Visual. Comput. Graphics

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Fig. 1. Many real-world volume data sets are sparse, lending appeal to rendering and processing techniques that benefit from such a property. Using our novel, storage-efficient data structure allows us to efficiently store such data sets as bricked textures on the GPU. From left to right: Stagbeetle (832 × 832 × 494, bricksize 7 3 , 5.01% non-empty, 245.5KB index); Pawpawsaurus Campbelli skull (958 × 646 × 1088, bricksize 15 3 , 15.1% non-empty, 50.21KB index); Angiography (416 × 512 × 112, bricksize 3 3 , 2.27% non-empty, 220.5KB index); Present (492 × 492 × 442, bricksize 7 3 , 17.3% non-empty, 78.80KB index). Our data structure introduces only minimal overhead in terms of memory and run-time, and it allows for efficient brick-level empty-space skipping.Abstract-In this paper we present a novel GPU-based data structure for spatial indexing. Based on Fenwick trees-a special type of binary indexed trees-our data structure allows construction in linear time. Updates and prefixes can be computed in logarithmic time, whereas point queries require only constant time on average. Unlike competing data structures such as summed-area tables and spatial hashing, our data structure requires a constant amount of bits for each data element, and it offers unconstrained point queries. This property makes our data structure ideally suited for applications requiring unconstrained indexing of large data, such as block-storage of large and block-sparse volumes. Finally, we provide asymptotic bounds on both run-time and memory requirements, and we show applications for which our new data structure is useful.

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JiTTree: A Just-in-Time Compiled Sparse GPU Volume Data Structure

Cited by 15 publications

References 26 publications

Universes and simulations: Civilizational development in nested embedding

Universes and simulations: Civilizational development in nested embedding

SkiMap: An efficient mapping framework for robot navigation

A Versatile and Efficient GPU Data Structure for Spatial Indexing

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