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Multilevel Performance Evaluation of Nvidia Grid VCA Using Iray and V-Ray Rendering Engines in 3DS Max Design

Received: 22 March 2018     Accepted: 4 April 2018     Published: 5 May 2018
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Abstract

High performance computing is increasingly common in technological industries and there are many different solutions available on the market. Determining which computing solution is most cost-effective can be difficult. This study outlines the performance between a single-user, traditional high-performance workstation and a multi-user, virtualized workstation. Along with this direct performance comparison, the impacts of virtualization on rendering performance, GPUs, and the technological industry is evaluated in this study. Through the repeated rendering of two different Computer-Aided Design (CAD) models under varying test scenarios, a pool of data including render times and image quality is collected and analyzed. Two phenomena are observed and explained. One is a diminishing return in GPU power output that is observed after allocating four or more GPUs to a single rendering task. The second is a noticeable point of image-noise convergence during a render that could potentially be calculated and exploited to make rendering more time-efficient. These discoveries may impact the effectiveness of virtual GPU scalability and make time-consuming rendering more efficient for industry users. The NVIDIA GRID Visual Computing Appliance (VCA) is found to be cost effective for research laboratories that have several users with diverse needs.

Published in Internet of Things and Cloud Computing (Volume 6, Issue 2)
DOI 10.11648/j.iotcc.20180602.11
Page(s) 36-48
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2018. Published by Science Publishing Group

Keywords

Rendering, Virtualization, Nvidia Grid Visual Computing Appliance, Graphics Processing Unit Computing, Iray, V-Ray

References
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Cite This Article
  • APA Style

    Kenneth Ritter III, Aaron Morgan, Charles Taylor, Terrence Chambers. (2018). Multilevel Performance Evaluation of Nvidia Grid VCA Using Iray and V-Ray Rendering Engines in 3DS Max Design. Internet of Things and Cloud Computing, 6(2), 36-48. https://doi.org/10.11648/j.iotcc.20180602.11

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    ACS Style

    Kenneth Ritter III; Aaron Morgan; Charles Taylor; Terrence Chambers. Multilevel Performance Evaluation of Nvidia Grid VCA Using Iray and V-Ray Rendering Engines in 3DS Max Design. Internet Things Cloud Comput. 2018, 6(2), 36-48. doi: 10.11648/j.iotcc.20180602.11

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    AMA Style

    Kenneth Ritter III, Aaron Morgan, Charles Taylor, Terrence Chambers. Multilevel Performance Evaluation of Nvidia Grid VCA Using Iray and V-Ray Rendering Engines in 3DS Max Design. Internet Things Cloud Comput. 2018;6(2):36-48. doi: 10.11648/j.iotcc.20180602.11

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  • @article{10.11648/j.iotcc.20180602.11,
      author = {Kenneth Ritter III and Aaron Morgan and Charles Taylor and Terrence Chambers},
      title = {Multilevel Performance Evaluation of Nvidia Grid VCA Using Iray and V-Ray Rendering Engines in 3DS Max Design},
      journal = {Internet of Things and Cloud Computing},
      volume = {6},
      number = {2},
      pages = {36-48},
      doi = {10.11648/j.iotcc.20180602.11},
      url = {https://doi.org/10.11648/j.iotcc.20180602.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.iotcc.20180602.11},
      abstract = {High performance computing is increasingly common in technological industries and there are many different solutions available on the market. Determining which computing solution is most cost-effective can be difficult. This study outlines the performance between a single-user, traditional high-performance workstation and a multi-user, virtualized workstation. Along with this direct performance comparison, the impacts of virtualization on rendering performance, GPUs, and the technological industry is evaluated in this study. Through the repeated rendering of two different Computer-Aided Design (CAD) models under varying test scenarios, a pool of data including render times and image quality is collected and analyzed. Two phenomena are observed and explained. One is a diminishing return in GPU power output that is observed after allocating four or more GPUs to a single rendering task. The second is a noticeable point of image-noise convergence during a render that could potentially be calculated and exploited to make rendering more time-efficient. These discoveries may impact the effectiveness of virtual GPU scalability and make time-consuming rendering more efficient for industry users. The NVIDIA GRID Visual Computing Appliance (VCA) is found to be cost effective for research laboratories that have several users with diverse needs.},
     year = {2018}
    }
    

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    AU  - Kenneth Ritter III
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    Y1  - 2018/05/05
    PY  - 2018
    N1  - https://doi.org/10.11648/j.iotcc.20180602.11
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    AB  - High performance computing is increasingly common in technological industries and there are many different solutions available on the market. Determining which computing solution is most cost-effective can be difficult. This study outlines the performance between a single-user, traditional high-performance workstation and a multi-user, virtualized workstation. Along with this direct performance comparison, the impacts of virtualization on rendering performance, GPUs, and the technological industry is evaluated in this study. Through the repeated rendering of two different Computer-Aided Design (CAD) models under varying test scenarios, a pool of data including render times and image quality is collected and analyzed. Two phenomena are observed and explained. One is a diminishing return in GPU power output that is observed after allocating four or more GPUs to a single rendering task. The second is a noticeable point of image-noise convergence during a render that could potentially be calculated and exploited to make rendering more time-efficient. These discoveries may impact the effectiveness of virtual GPU scalability and make time-consuming rendering more efficient for industry users. The NVIDIA GRID Visual Computing Appliance (VCA) is found to be cost effective for research laboratories that have several users with diverse needs.
    VL  - 6
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Author Information
  • College of Engineering, University of Louisiana at Lafayette, Lafayette, USA

  • College of Engineering, University of Louisiana at Lafayette, Lafayette, USA

  • College of Engineering, University of Louisiana at Lafayette, Lafayette, USA

  • College of Engineering, University of Louisiana at Lafayette, Lafayette, USA

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