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Blueprint species:

Use Case Attributes	Description	Informational
Type	New Blueprint for VR/AR on the Network Edge
Blueprint Family	Integrated Edge Cloud (IEC)
Use Case

AR/VR Ecosystem

Deployment of generic edge end and cloud environment for VR/AR cloud streaming
Blueprint proposed Name	IEC Type 4: AR/VR oriented Internet Edge Stack for Integrated Edge Cloud (IEC) Blueprint Family
Initial POD Cost (capex)	NVIDIA

Tesla K80

RTX GPUs

Chelsio T580-CR NICs

Scale & Type

The test configuration consists of 2 machines connected back-to-back using single port: a Server and Client, each with Xeon processor clocked at 3.70GHz (HT enabled), with 64GB of RAM and Ubuntu operating system. Standard MTU of 1500B is configured. One Chelsio T580-CR and Tesla K80 GPU adapter is installed in each system with Chelsio GPUDirect RDMA driver v1.0.0.0, CUDA v6.5, OpenMPI v1.8.4 (with CUDA support), OSU micro benchmarking tools v4.4.1 and nVIDIA peer memory driver.

[root@host]# /opt/ompi-1.8.4-gdr/bin/mpirun --allow-run-as-root -mca btl_openib_want_cuda_gdr <0/1> -np 2 -host -npernode 1 -mca btl openib,sm,self -mca btl_openib_if_include cxgb4_0:1 --mca btl_openib_cuda_rdma_limit 65538 -mca btl_openib_receive_queues P,131072,64 -x CUDA_VISIBILE_DEVICES=0 /root/osu-micro-benchmarks4.4.1/mpi/pt2pt/ -d cuda D D

Applications

Augmented reality and virtual reality for multi-party gaming

Remote conferencing

Interactive immersive films (especially SLAM and ray tracing for large scence)

Power and memory restrictions

N/A

Infrastructure orchestration

Need video caching for tenants

Need memcached serving as block layer for consistency

Need sync between GPU and CPU

Need load balancing server and server (a layer above memcached)

Need load balancing btw GPU and CPU

SDN

Calico and K8s, Memcached load balancer

Workload Type

Containers for SLAM raytracing and video caching, other techniques could be offload to Edge includes but not limited to:

Modeling (Modeling describes the process of forming the shape of an object)

[Funk03]Funkhouser T, Min P, Kazhdan M, Chen J, Halderman A, Dobkin D, Jacobs D. A search engine for 3D models. ACM Transactions on Graphics 2003; 22(1): 83–105.*[Hopp96]H. Hoppe, "Progressive Meshes," SIGGRAPH96, pp. 99-108.[Lore87]W. Lorensen and H. Cline, "Marching Cubes: A High Resolution 3D Surface Construction Algorithm," SIGGRAPH 87, pp. 163-169.[Funk03]Funkhouser T, Min P, Kazhdan M, Chen J, Halderman A, Dobkin D, Jacobs D. A search engine for 3D models. ACM Transactions on Graphics 2003; 22(1): 83–105.[Lore87]W. Lorensen and H. Cline, "Marching Cubes: A High Resolution 3D Surface Construction Algorithm," SIGGRAPH 87, pp. 163-169.2.Anti-aliasing*[Cook86]R. Cook, "Stochastic Sampling in Computer Graphics," ACM TOG, (January 1986), pp. 51-72.3.Compositing*[Port84]Porter, T. and Duff, T. "Compositing Digital Images," SIGGRAPH '84, pp 253-259.*[Zong99]D. Zongker, D. Werner, B. Curless, and D. Salesin. “Environment Matting and Compositing”, SIGGRAPH ’99, pp. 205-214.*[Pére03]Pérez, P., Gangnet, M., and Blake, A. 2003. "Poisson image editing". ACM Trans. Graph. (SIGGRAPH 2003) 22, 3 (Jul. 2003), 313-318.4.Texture[Perl85]K. Perlin, "An Image Synthesizer". SIGGRAPH 85, pp. 287-296.*[Heck86]P. Heckbert, "Survey of Texture Mapping," IEEE CG&A (November 1986), pp. 56-67.*[Sims91]K. Sims, “Artificial Evolution for Computer Graphics,” SIGGRAPH 91, pp. 319-328.[Scho00]Schodl A., Szeliski R., Salesin D., Essai.: "Video textures". In ACM Transactions on Graphics (ACM SIGGRAPH 2000) (2000), vol. 19, pp. 489–498.*[WEI00]Wei, L.-Y., and Levoy, M. "Fast texture synthesis using tree-structured vector quantization". In Proceedings of SIGGRAPH 2000 (July 2000), pp. 479–488.[Perl85]K. Perlin, "An Image Synthesizer". SIGGRAPH 85, pp. 287-296.[Scho00]Schodl A., Szeliski R., Salesin D., Essai.: "Video textures". In ACM Transactions on Graphics (ACM SIGGRAPH 2000) (2000), vol. 19, pp. 489–498.5.Image-based Rendering*[Debe96]P. Debevec, C. Taylor, and J. Malik, “Modeling and Rendering Architecture from Photographs: A Hybrid Geometry- and Image-Based Approach”, SIGGRAPH ’96, pp. 11-20.[McMi95]L. McMillan and G. Bishop, “Plenoptic Modeling: An Image-Based Rendering System”, SIGGRAPH ’95, pp. 39-46.[Levo96]M. Levoy and P. Hanrahan, “Light Field Rendering”,SIGGRAPH ’96, pp. 31-42.[McMi95]L. McMillan and G. Bishop, “Plenoptic Modeling: An Image-Based Rendering System”, SIGGRAPH ’95, pp. 39-46.[Levo96]M. Levoy and P. Hanrahan, “Light Field Rendering”,SIGGRAPH ’96, pp. 31-42.6.GPU*[Purc02]T. Purcell, I. Buck, W. Mark, and P. Hanrahan, "Ray Tracing on Programmable Graphics Hardware", SIGGRAPH '02, pp. 703-712.[Krug03]Krüger, J., Westermann, R. 2003. “Acceleration Techniques for GPU-based Volume Rendering”. Proceedings of IEEE Visualization 2003, 287-292,7.Rendering and Illumination Models*[Cook81]R. Cook and K. Torrance, "A Reflectance Model for Computer Graphics," SIGGRAPH 81, pp. 307-316.*[Kaji86]J. Kajiya, "The Rendering Equation," SIGGRAPH 86, pp. 143-150.*[Cohe88]M. Cohen, S. Chen, J. Wallace, and D. Greenberg, "A Progressive Refinement Approach to Fast Radiosity Image Generation," SIGGRAPH 88, pp. 75-84.[Jens98]H. Jensen and P. Christensen. “Efficient Simulation of Light Transport in Scenes With Participating Media Using Photon Maps”, SIGGRAPH ’98, pp. 311-320.*[Sloa02]P. Sloan, J. Kautz, and J. Snyder. "Precomputed radiance transfer for real-time rendering in dynamic, low-frequency lighting environments". ACM Transactions on Graphics (Proceedings of SIGGRAPH 2002), 21(3):527-–536, July 2002.8.Animation*[Bara98]D. Baraff and A. Witkin. “Large time steps in cloth simulation,” SIGGRAPH’98, pages43-54, 1998.*[Hahn88]J. Hahn, "Realistic Animation of Rigid Bodies". SIGGRAPH 88, pp. 299-308.[Witk88]A. Witkin and M. Kass, "Spacetime Constraints". SIGGRAPH 88, pp. 159-168.*[Brud95]A. Bruderlin and L. Williams, “Motion Signal Processing”, SIGGRAPH ’95, pp. 97-104.[Glei98]M. Gleicher, “Retargeting Motion to New Characters”, SIGGRAPH ’98, pp. 33-42.[Kova02]Kovar, L., Gleicher, M., and Pighin, F. 2002. “Motion graphs”. In Proceedings of the 29th Annual Conference on Computer Graphics and interactive Techniques (San Antonio, Texas, July 23 - 26, 2002). SIGGRAPH '02. ACM Press, New York, NY, 473-482.9.Sound*[Taka92]T. Takala and J. Hahn, "Sound Rendering," SIGGRAPH 92, pp. 211-220.

10. Non-Photorealistic Rendering

*[Meie96]B. Meier, “Painterly Rendering for Animation”, SIGGRAPH ’96, pp. 477-484.*[Prau01]E. Praun, H. Hoppe, M. Webb, and A. Finkelstein, "Real-Time Hatching", SIGGRAPH '01, pp. 581-586

11. Point Based Rendering

[Rusi00]S. Rusinkiewicz, M. Levoy, "QSplat: a multiresolution point rendering system for large meshes", Computer Graphics, (SIGGRAPH 2000 Proceedings), pp. 343–352[Pfis00]H. Pfister, M. Zwicker, J. Barr, and M. Gross, "Surfels: Surface Elements as Rendering Primitives", SIGGRAPH '00, pp. 335-342.

12. HDR and Tone Mapping

*[Debe97]Paul E. Debevec , Jitendra Malik, "Recovering high dynamic range radiance maps from photographs", Proceedings of the 24th annual conference on Computer graphics and interactive techniques, p.369-378, August 1997 *[Rein02]Reinhard, E., Stark, M., Shirley, P., and Ferwerda, J. 2002. "Photographic tone reproduction for digital images". ACM Trans. Graph. 21, 3 (Jul. 2002), 267-276

13. Computational Photography

[Agar04]Agarwala, A., Dontcheva, M., Agrawala, M., Drucker, S., Colburn, A., Curless, B., Salesin, D., and Cohen, M. 2004. Interactive digital photomontage. ACM Trans. Graph. 23, 3 (Aug. 2004), 294-302. 14.Visualization*[Dreb88]R. Drebin, L. Carpenter, and P. Hanrahan, "Volume Rendering," SIGGRAPH 88, pp. 65-74.[Levo88]Levoy, M. 1988. “Display of Surfaces From Volume Data”. IEEE Computer Graphics and Applications. 8, 3 (May 1988), 29-37.[Bier93]Bier E.A., Stone M., Pier K., Buxton W., DeRose T.D. “Toolglass and magic lenses: the see-through interface” Int. Conf. on Computer Graphics and Interactive Techniques, Anaheim, CA, Pages: 73 – 80. 1993*[Dole03]Helmut Doleisch, Martin Gasser, Helwig Hauser. “Interactive feature specification for focus+context visualization of complex simulation data”. Proceedings of the symposium on Data visualization, Grenoble, France, Pages: 239 – 248, 2003.15.Medical Visualization[Knis02]Kniss, J.; Kindlmann, G.; Hansen, C., “Multidimensional transfer functions for interactive volume rendering”, IEEE Trans. on Visualization and Computer Graphics, 8: 3, Page(s):270 – 285, July-Sept. 2002.[Tory04]Tory, M.; Moller, T.; “Human factors in visualization research”. IEEE Transactions on Visualization and Computer Graphics, 10: 1, Page(s):72 – 84, Jan.-Feb. 2004.*[Beye07]Beyer, J. Hadwiger, M. Wolfsberger, S. Buhler, K. “High-Quality Multimodal Volume Rendering for Preoperative Planning of Neurosurgical Interventions.” IEEE Trans. on Visualization and Computer Graphics, 13: 6, page(s): 1696-1703, Nov.-Dec. 2007*[Svak09]Svakhine, N.A. Ebert, D.S. Andrews, W.M., “Illustration-Inspired Depth Enhanced Volumetric Medical Visualization” IEEE Trans. On Visualization and Computer Graphics, 15: 1, page(s): 77-86, Jan.-Feb. 2009.[Krug06]Kruger, J. Schneider, J. Westermann, R. “ClearView: An Interactive Context Preserving Hotspot Visualization Technique”, IEEE Trans. on Visualization and Computer Graphics, 12: 5, pp: 941-948, Sept.-Oct. 2006.

16. Image Guidance

[Azum97]Azuma, R. 1997. “A Survey of Augmented Reality”. Presence: Teleoperators and Virtual Environments. 6, 4 (Aug. 1997), 355-385[Grim96]Grimson, W. E. L., Ettinger, G. J., White, S. J., Lozano-P´erez, T., Wells III, W. M., and Kikinis, R. (1996). An automatic registration method for frameless stereotaxy, image guided surgery, and enhanced reality visualization. IEEE Transactions on medical imaging, 15(2), 129–140.[Helf07]Helferty JP, Sherbondy AJ, Kiraly AP, Higgins WE. Computer-based system for the virtual-endoscopic guidance of bronchoscopy. Computer Vision and Image Understanding Oct-Nov; 2007 108(1–2):171–187.[Jin09]"Image Guided Medialization Laryngoplasty," Journal of Computer Animation and Virtual Worlds, Vol. 20, No. 1, January/February 2009 (Ge Jin, Nakhoon Baek, James Hahn, Steven Bielamowicz, Rajat Mittal, Raymond Walsh).[Pete06]Terry M Peters. “Image-guidance for surgical procedures”, Phys. Med. Biol.51 R505-R540, 2006.

17. Registration

[Besl92]Besl PJ, McKay ND. "A method for registration of 3-D shapes," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 14, no. 2, pp. 239-256, 1992.[Aude00]Audette, M.A., Ferrie, F.P., Peters, T.M., "An algorithmic overview of surface registration techniques for medical imaging," Medical Image Analysis, vol. 4, pp. 201-217, 2000.[Thir98]Thirion, J.P., "Image matching as a diffusion process: An analogy with Maxwell's demons," Med. Image Anal., vol. 2, no. 3, pp. 243-260, 1998.

18. Segmentation

*[Kass87]M. Kass, A. Witkin, and D. Terzopoulos, “Snakes: Active Contour Models” International Journal of Computer Vision, 1(4): 321-331, 1987. *[Mall95]Malladi,R., Sethian, J.A., Vemuri, B.C., Shape modeling with front propagation: a level set approach, IEEE Trans. on Pattern Analysis and Machine Intelligence, vol.17, no. 2, pp. 158-175, 1995.*[Seth96]Sethian, J.A., "A fast marching level set method for monotonically advancing fronts," Proc Natl Acad Sci U S A, vol. 93, no. 4, pp. 1591-5, 1996.

Additional Details

NVIDIA Tesla K80 GPUs (Tesla and Quadro GPUs), using kernel module GPUDirect RDMA. https://docs.nvidia.com/cuda/gpudirect-rdma/index.html https://developer.nvidia.com/gpudirect

Silberstein, M., Kim, S., Huh, S., Zhang, X., Hu, Y., Wated, A., & Witchel, E. (2016). GPUnet: Networking abstractions for GPU programs. ACM Transactions on Computer Systems (TOCS), 34(3), 9. https://github.com/ut-osa/gpunet

Generic blueprint PoC: One master node and up to 5 worker nodes with mixed Linux and Windows OS Each server, x86/ARM server with nVidia RTX GPUs (Titan or GeForce) and Chelsio T580-CR NIC Large scale deployment: Number of servers, x86/ARM server or deep edge class, is site dependent (footprint) vGPU and federation supported class, e.g. NVIDIA Tesla K80 GPUs;
Applications	Generic blueprint POD: Small scale cloud AR/VR rendering farm with generic SO. Production/commercial service: Consumer applications: High performance premium gaming, 3D video for movies, live concerts, events, LBE, etc. Enterprise applications: training/education, product design collaboration, manufacturing, maintenance, data analytical etc,
Power and memory restrictions	N/A
Infrastructure orchestration	Docker 1.13.1 or above and K8s 1.10.2 or above- Container Orchestration, VMWare VM OS - Ubuntu 16.x, windows server 2019 Under Cloud Orchestration - Airship v1.0 (TBD)
SDN	Calico and K8s, Memcached load balancer
Workload Type	VR and AR applications with split rendering runtime running inside Containers or VM
Additional Details	The test configuration consists of 2 machines connected back-to-back using single port: a master and worker node, each with TBD processor clocked at TBD GHz, with TBD GB of RAM and Ubuntu operating system for master, windows server 2019 or later for worker. MTU of 1450B is configured (to compensate for GTP tunnel header). One Chelsio T580-CR and TBD GPU adapter is installed in each system with Chelsio GPUDirect RDMA driver v1.0.0.0, CUDA v6.5, OpenMPI v1.8.4 (with CUDA support), OSU micro benchmarking tools v4.4.1 and nVIDIA peer memory driver.

Attachments:

View file

name	vr-wpy-v2.pptx
height	250

View file

name

HTC for Akraino 5GXRSIG UC3- v5 submitted to Akraino for IEC Type 4 review-v2.pdf
height 250

Committer	Committer Company	Committer Contact Info	Committer Bio	Committer Picture	Self Nominate for PTL (Y/N)
Tina Tsou	Arm
Wenhui Zhang	PSU				N
Wenping Ying	HTC	wenping_ying@htc.com			N
Ryan Anderson	IBM	rranders@us.ibm

.comWenping YingHTCwenping_ying@htc

.com

Contributor

Company

Contributor Contact Info

Contributor Bio

Contributor Picture

Self Nominate for PTL (Y/N)

Christos Kolias

Orange

christos.kolias@orange.com

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