scholarly journals Acceleration of ray tracing method using predictive evaluation and GPGPU technology

2014 ◽  
Vol 4 (3) ◽  
Author(s):  
Branislav Sobota ◽  
Štefan Korečko ◽  
Csaba Szabó ◽  
František Hrozek
Keyword(s):  
Ray Tracing ◽  
Graphics Processing Units ◽  
Computation Time ◽  
General Purpose ◽  
Ray Tracing Method ◽  
Parallel Solution ◽  
Graphics Processing ◽  
Tracing Method ◽  
Selection Of ◽  
Parallel Ray Tracing

AbstractRay tracing is one of computer graphics methods for achieving the most realistic outputs. Its main disadvantage is high computation demands. Removal of this disadvantage is possible using parallelization due to the fact that the ray tracing method is inherently parallel. Solution presented in this article uses GPGPU (general-purpose computing on graphics processing units) technology and a predictive evaluation for the acceleration of ray tracing method. The CUDA C was selected as a GPGPU language and it was used for a conversion of a raytracer core. The main reason for choosing this language was usage of the Tesla C1060 graphics card. The predictive evaluation of a scene was based on the fact that total computation time increases proportionally with resolution. This evaluation allows selection of the optimal scene division for the parallel ray tracing. In tests, proposed GPGPU solution reached accelerations up to 28.3× comparing to CPU.

scholarly journals Parallel SVD Algorithm for a Three-Diagonal Matrix on a Video Card Using the Nvidia CUDA Architecture

2021 ◽  
Vol 4 ◽  
pp. 16-22
Author(s):  
Mykola Semylitko ◽  
Gennadii Malaschonok
Keyword(s):  
Graphics Processing Units ◽  
Graphics Processing Unit ◽  
Computation Time ◽  
Application Programming Interface ◽  
General Purpose ◽  
Diagonal Matrix ◽  
Free Access ◽  
Processing Unit ◽  
Cuda Architecture ◽  
Graphics Processing

SVD (Singular Value Decomposition) algorithm is used in recommendation systems, machine learning, image processing, and in various algorithms for working with matrices which can be very large and Big Data, so, given the peculiarities of this algorithm, it can be performed on a large number of computing threads that have only video cards.CUDA is a parallel computing platform and application programming interface model created by Nvidia. It allows software developers and software engineers to use a CUDA-enabled graphics processing unit for general purpose processing – an approach termed GPGPU (general-purpose computing on graphics processing units). The GPU provides much higher instruction throughput and memory bandwidth than the CPU within a similar price and power envelope. Many applications leverage these higher capabilities to run faster on the GPU than on the CPU. Other computing devices, like FPGAs, are also very energy efficient, but they offer much less programming flexibility than GPUs.The developed modification uses the CUDA architecture, which is intended for a large number of simultaneous calculations, which allows to quickly process matrices of very large sizes. The algorithm of parallel SVD for a three-diagonal matrix based on the Givents rotation provides a high accuracy of calculations. Also the algorithm has a number of optimizations to work with memory and multiplication algorithms that can significantly reduce the computation time discarding empty iterations.This article proposes an approach that will reduce the computation time and, consequently, resources and costs. The developed algorithm can be used with the help of a simple and convenient API in C ++ and Java, as well as will be improved by using dynamic parallelism or parallelization of multiplication operations. Also the obtained results can be used by other developers for comparison, as all conditions of the research are described in detail, and the code is in free access.

Method for Reduction of Field Computation Time for Discrete Ray Tracing Method

2014 ◽  
Vol E97.C (3) ◽  
pp. 198-206 ◽  
Author(s):  
Masafumi TAKEMATSU ◽  
Junichi HONDA ◽  
Yuki KIMURA ◽  
Kazunori UCHIDA
Keyword(s):  
Ray Tracing ◽  
Computation Time ◽  
Ray Tracing Method ◽  
Field Computation ◽  
Tracing Method

The paraxial ray method

Geophysics ◽  
1987 ◽  
Vol 52 (12) ◽  
pp. 1639-1653 ◽  
Author(s):  
Wafik B. Beydoun ◽  
Timothy H. Keho
Keyword(s):  
Wave Field ◽  
Ray Tracing ◽  
Heterogeneous Media ◽  
Computation Time ◽  
Ray Method ◽  
Ray Tracing Method ◽  
Paraxial Ray ◽  
The Cost ◽  
Seismic Wave Field ◽  
Tracing Method

The paraxial ray method is an economical way of computing approximate Green’s functions in heterogeneous media. The method uses information from the standard dynamic ray‐tracing method to extrapolate the seismic wave field at receivers in the neighborhood of a ray so that two‐point ray tracing is not required. Applicability conditions are explicit: they define where asymptotic (high‐frequency) methods are valid, and how far away from the ray the extrapolation remains accurate. Increasing the density of the ray fan improves accuracy but increases computation time. However, since reasonable accuracy is obtained with relatively few rays, the method yields results similar to the two‐point ray‐tracing method, but at a fraction of the cost. Examples of wave‐field extrapolation from a ray to neighboring receivers show that traveltime extrapolation is more accurate than amplitude extrapolation. Accuracy, robustness, and efficiency tests, comparing paraxial ray synthetic seismograms with acoustic finite‐difference and elastic discrete‐wavenumber synthetics, are judged very satisfactory.

Field Estimation in Tunnel and Underground by Ray Tracing Method

2000 ◽  
Vol 54 (3) ◽  
pp. 46-56
Author(s):  
K. Uchida ◽  
D. Da ◽  
C. K. Lee ◽  
T. Matsunaga ◽  
T. Imai ◽  
...  
Keyword(s):  
Ray Tracing ◽  
Ray Tracing Method ◽  
Field Estimation ◽  
Tracing Method

scholarly journals DSPSR: Digital Signal Processing Software for Pulsar Astronomy

2011 ◽  
Vol 28 (1) ◽  
pp. 1-14 ◽  
Author(s):  
W. van Straten ◽  
M. Bailes
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Graphics Processing Units ◽  
High Performance ◽  
Digital Signal ◽  
General Purpose ◽  
Design Decisions ◽  
Extensive Range ◽  
Processing Software ◽  
Graphics Processing

Abstractdspsr is a high-performance, open-source, object-oriented, digital signal processing software library and application suite for use in radio pulsar astronomy. Written primarily in C++, the library implements an extensive range of modular algorithms that can optionally exploit both multiple-core processors and general-purpose graphics processing units. After over a decade of research and development, dspsr is now stable and in widespread use in the community. This paper presents a detailed description of its functionality, justification of major design decisions, analysis of phase-coherent dispersion removal algorithms, and demonstration of performance on some contemporary microprocessor architectures.

A GPU-Accelerated ray-tracing method for determining radiation view factors in multi-junction thermoelectric generators

Energy ◽  
2021 ◽  
Vol 228 ◽  
pp. 120438
Author(s):  
Asher J. Hancock ◽  
Laura B. Fulton ◽  
Justin Ying ◽  
Corey E. Clifford ◽  
Shervin Sammak ◽  
...  
Keyword(s):  
Ray Tracing ◽  
Thermoelectric Generators ◽  
Ray Tracing Method ◽  
View Factors ◽  
Tracing Method
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