Effect of short-term exposure to stereoscopic three-dimensional flight displays on real-world depth perception

High-fidelity color pictorial displays that incorporate depth cues in the display elements are currently available. Depth cuing applied to advanced head-down flight display concepts potentially enhances the pilot's situational awareness and improves task performance. Depth cues provided by stereopsis exhibit constraints that must be fully understood so depth cuing enhancements can be adequately realized and exploited. A fundamental issue (the goal of this investigation) is whether the use of head-down stereoscopic displays in flight applications degrade the real-world depth perception of pilots using such displays. Stereoacuity tests are used in this study as the measure of interest. Eight pilots flew repeated simulated landing approaches using both nonstereo and stereo 3-D head-down pathway-in-the-sky displays. At this decision height of each approach (where the pilot changes to an out-the-window view to obtain real-world visual references) the pilots changed to a stereoacuity test that used real objects. Statistical analysis of stereoacuity measures (data for a control condition of no exposure to any electronic flight display compared with data for changes from nonstereo and from stereo displays) reveals no significant differences for any of the conditions. Therefore, changing from short-term exposure to a head-down stereo display has no more effect on real-world relative depth perception than does changing from a nonstereo display. However, depth perception effects based on sized and distance judgements and on long-term exposure remain issues to be investigated

The development of local solar irradiance for outdoor computer graphics rendering

Atmospheric effects are approximated by solving the light transfer equation, LTE, of a given viewing path. The resulting accumulated spectral energy (its visible band) arriving at the observer’s eyes, defines the colour of the object currently on the line of sight. Due to the convenience of using a single rendering equation to solve the LTE for daylight sky and distant objects (aerial perspective), recent methods had opt for a similar kind of approach. Alas, the burden that the real-time calculation brings to the foil had forced these methods to make simplifications that were not in line with the actual world observation. Consequently, the results of these methods are laden with visual-errors. The two most common simplifications made were: i) assuming the atmosphere as a full-scattering medium only and ii) assuming a single density atmosphere profile. This research explored the possibility of replacing the real-time calculation involved in solving the LTE with an analytical-based approach. Hence, the two simplifications made by the previous real-time methods can be avoided. The model was implemented on top of a flight simulator prototype system since the requirements of such system match the objectives of this study. Results were verified against the actual images of the daylight skies. Comparison was also made with the previous methods’ results to showcase the proposed model strengths and advantages over its peers

Computational advances in gravitational microlensing: a comparison of CPU, GPU, and parallel, large data codes

To assess how future progress in gravitational microlensing computation at high optical depth will rely on both hardware and software solutions, we compare a direct inverse ray-shooting code implemented on a graphics processing unit (GPU) with both a widely-used hierarchical tree code on a single-core CPU, and a recent implementation of a parallel tree code suitable for a CPU-based cluster supercomputer. We examine the accuracy of the tree codes through comparison with a direct code over a much wider range of parameter space than has been feasible before. We demonstrate that all three codes present comparable accuracy, and choice of approach depends on considerations relating to the scale and nature of the microlensing problem under investigation. On current hardware, there is little difference in the processing speed of the single-core CPU tree code and the GPU direct code, however the recent plateau in single-core CPU speeds means the existing tree code is no longer able to take advantage of Moore's law-like increases in processing speed. Instead, we anticipate a rapid increase in GPU capabilities in the next few years, which is advantageous to the direct code. We suggest that progress in other areas of astrophysical computation may benefit from a transition to GPUs through the use of "brute force" algorithms, rather than attempting to port the current best solution directly to a GPU language -- for certain classes of problems, the simple implementation on GPUs may already be no worse than an optimised single-core CPU version.Comment: 11 pages, 4 figures, accepted for publication in New Astronom

A sparse octree gravitational N-body code that runs entirely on the GPU processor

We present parallel algorithms for constructing and traversing sparse octrees on graphics processing units (GPUs). The algorithms are based on parallel-scan and sort methods. To test the performance and feasibility, we implemented them in CUDA in the form of a gravitational tree-code which completely runs on the GPU.(The code is publicly available at: http://castle.strw.leidenuniv.nl/software.html) The tree construction and traverse algorithms are portable to many-core devices which have support for CUDA or OpenCL programming languages. The gravitational tree-code outperforms tuned CPU code during the tree-construction and shows a performance improvement of more than a factor 20 overall, resulting in a processing rate of more than 2.8 million particles per second.Comment: Accepted version. Published in Journal of Computational Physics. 35 pages, 12 figures, single colum

A Framework for Megascale Agent Based Model Simulations on Graphics Processing Units

Agent-based modeling is a technique for modeling dynamic systems from the bottom up. Individual elements of the system are represented computationally as agents. The system-level behaviors emerge from the micro-level interactions of the agents. Contemporary state-of-the-art agent-based modeling toolkits are essentially discrete-event simulators designed to execute serially on the Central Processing Unit (CPU). They simulate Agent-Based Models (ABMs) by executing agent actions one at a time. In addition to imposing an un-natural execution order, these toolkits have limited scalability. In this article, we investigate data-parallel computer architectures such as Graphics Processing Units (GPUs) to simulate large scale ABMs. We have developed a series of efficient, data parallel algorithms for handling environment updates, various agent interactions, agent death and replication, and gathering statistics. We present three fundamental innovations that provide unprecedented scalability. The first is a novel stochastic memory allocator which enables parallel agent replication in O(1) average time. The second is a technique for resolving precedence constraints for agent actions in parallel. The third is a method that uses specialized graphics hardware, to gather and process statistical measures. These techniques have been implemented on a modern day GPU resulting in a substantial performance increase. We believe that our system is the first ever completely GPU based agent simulation framework. Although GPUs are the focus of our current implementations, our techniques can easily be adapted to other data-parallel architectures. We have benchmarked our framework against contemporary toolkits using two popular ABMs, namely, SugarScape and StupidModel.GPGPU, Agent Based Modeling, Data Parallel Algorithms, Stochastic Simulations

Playing for Data: Ground Truth from Computer Games

Recent progress in computer vision has been driven by high-capacity models trained on large datasets. Unfortunately, creating large datasets with pixel-level labels has been extremely costly due to the amount of human effort required. In this paper, we present an approach to rapidly creating pixel-accurate semantic label maps for images extracted from modern computer games. Although the source code and the internal operation of commercial games are inaccessible, we show that associations between image patches can be reconstructed from the communication between the game and the graphics hardware. This enables rapid propagation of semantic labels within and across images synthesized by the game, with no access to the source code or the content. We validate the presented approach by producing dense pixel-level semantic annotations for 25 thousand images synthesized by a photorealistic open-world computer game. Experiments on semantic segmentation datasets show that using the acquired data to supplement real-world images significantly increases accuracy and that the acquired data enables reducing the amount of hand-labeled real-world data: models trained with game data and just 1/3 of the CamVid training set outperform models trained on the complete CamVid training set.Comment: Accepted to the 14th European Conference on Computer Vision (ECCV 2016

Memory transfer optimization for a lattice Boltzmann solver on Kepler architecture nVidia GPUs

The Lattice Boltzmann method (LBM) for solving fluid flow is naturally well suited to an efficient implementation for massively parallel computing, due to the prevalence of local operations in the algorithm. This paper presents and analyses the performance of a 3D lattice Boltzmann solver, optimized for third generation nVidia GPU hardware, also known as `Kepler'. We provide a review of previous optimisation strategies and analyse data read/write times for different memory types. In LBM, the time propagation step (known as streaming), involves shifting data to adjacent locations and is central to parallel performance; here we examine three approaches which make use of different hardware options. Two of which make use of `performance enhancing' features of the GPU; shared memory and the new shuffle instruction found in Kepler based GPUs. These are compared to a standard transfer of data which relies instead on optimised storage to increase coalesced access. It is shown that the more simple approach is most efficient; since the need for large numbers of registers per thread in LBM limits the block size and thus the efficiency of these special features is reduced. Detailed results are obtained for a D3Q19 LBM solver, which is benchmarked on nVidia K5000M and K20C GPUs. In the latter case the use of a read-only data cache is explored, and peak performance of over 1036 Million Lattice Updates Per Second (MLUPS) is achieved. The appearance of a periodic bottleneck in the solver performance is also reported, believed to be hardware related; spikes in iteration-time occur with a frequency of around 11Hz for both GPUs, independent of the size of the problem.Comment: 12 page

Development of a GPU-based Monte Carlo dose calculation code for coupled electron-photon transport

Monte Carlo simulation is the most accurate method for absorbed dose calculations in radiotherapy. Its efficiency still requires improvement for routine clinical applications, especially for online adaptive radiotherapy. In this paper, we report our recent development on a GPU-based Monte Carlo dose calculation code for coupled electron-photon transport. We have implemented the Dose Planning Method (DPM) Monte Carlo dose calculation package (Sempau et al, Phys. Med. Biol., 45(2000)2263-2291) on GPU architecture under CUDA platform. The implementation has been tested with respect to the original sequential DPM code on CPU in phantoms with water-lung-water or water-bone-water slab geometry. A 20 MeV mono-energetic electron point source or a 6 MV photon point source is used in our validation. The results demonstrate adequate accuracy of our GPU implementation for both electron and photon beams in radiotherapy energy range. Speed up factors of about 5.0 ~ 6.6 times have been observed, using an NVIDIA Tesla C1060 GPU card against a 2.27GHz Intel Xeon CPU processor.Comment: 13 pages, 3 figures, and 1 table. Paper revised. Figures update