ISSN 2079-3537      

 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                                                                                             
Scientific Visualization
Issue Year: 2014
Quarter: 4
Volume: 6
Number: 4
Pages: 1-10
Article Name: APPLICATION OF NVIDIA OPTIX TO CARRY OUT NUMERICAL EXPERIMENTS
Authors: V.A. Debelov (Russian Federation)
  The paper is recommended by program committee of 24th International Conference on Computer Graphics and Vision GraphiCon’2014.
Address: V.A. Debelov
debelov@oapmg.sscc.ru
Institute of Computational Mathematics and Mathematical Geophysics SB RAS, Novosibirsk, Russia
Abstract: A lot of research programs are implemented in order to carry out numerical experiments while debugging of an algorithm or obtaining different data of an investigated computer model. As a rule the data are visualized by means of scientific visualization tools. In these paper the author considers reasons to apply Nvidia OptiX as a tool to carry out numerical experiments using graphical processing units (GPU) GeForce.
Although OptiX is built on CUDA and runs on a graphical unit, a researcher does not have to know programming elements such as an architecture of GPU, CUDA, OpenGL, DirectX. By the way, a knowledge of programming for a cluster – for example, MPI (Message Passing Interface) – is also not needed.
OptiX is considered as an effective tool to control a run of a loop

    i = 0 .. N
        j = 0 .. M
          k = 0 .. K
            f(i, j, k, <additional parameters >),
where f(i, j, k, < additional parameters >) is an algoritm being debugged or tested computer model.
From the author’s point of view GPU considered can be imagined as a desktop cluster including multiple processors working in parallel on shared memory. A researcher can use a PC in parallel at his discretion while his program runs on GPU.
To justify a suggested approach the author shows with several tests a speedup rate of an OptiX program in comparison with a sequential program.
Language: Russian


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