NBCUni 9.5.23

GTC embraces machine learning and AI

By Mike McCarthy

I had the opportunity to attend GTC 2018, Nvidia‘s 9th annual technology conference in San Jose this week. GTC stands for GPU Technology Conference, and GPU stands for graphics processing unit, but graphics makes up a relatively small portion of the show at this point. The majority of the sessions and exhibitors are focused on machine learning and artificial intelligence.

And the majority of the graphics developments are centered around analyzing imagery, not generating it. Whether that is classifying photos on Pinterest or giving autonomous vehicles machine vision, it is based on the capability of computers to understand the content of an image. Now DriveSim, Nvidia’s new simulator for virtually testing autonomous drive software, dynamically creates imagery for the other system in the Constellation pair of servers to analyze and respond to, but that is entirely machine-to-machine imagery communication.

The main exception to this non-visual usage trend is Nvidia RTX, which allows raytracing to be rendered in realtime on GPUs. RTX can be used through Nvidia’s OptiX API, as well as Microsoft’s DirectX RayTracing API, and eventually through the open source Vulkan cross-platform graphics solution. It integrates with Nvidia’s AI Denoiser to use predictive rendering to further accelerate performance, and can be used in VR applications as well.

Nvidia RTX was first announced at the Game Developers Conference last week, but the first hardware to run it was just announced here at GTC, in the form of the new Quadro GV100. This $9,000 card replaces the existing Pascal-based GP100 with a Volta-based solution. It retains the same PCIe form factor, the quad DisplayPort 1.4 outputs and the NV-Link bridge to pair two cards at 200GB/s, but it jumps the GPU RAM per card from 16GB to 32GB of HBM2 memory. The GP100 was the first Quadro offering since the K6000 to support double-precision compute processing at full speed, and the increase from 3,584 to 5,120 CUDA cores should provide a 40% increase in performance, before you even look at the benefits of the 640 Tensor Cores.

Hopefully, we will see simpler versions of the Volta chip making their way into a broader array of more budget-conscious GPU options in the near future. The fact that the new Nvidia RTX technology is stated to require Volta architecture CPUs leads me to believe that they must be right on the horizon.

Nvidia also announced a new all-in-one GPU supercomputer — the DGX-2 supports twice as many Tesla V100 GPUs (16) with twice as much RAM each (32GB) compared to the existing DGX-1. This provides 81920 CUDA cores addressing 512GB of HBM2 memory, over a fabric of new NV-Link switches, as well as dual Xeon CPUs, Infiniband or 100GbE connectivity, and 32TB of SSD storage. This $400K supercomputer is marketed as the world’s largest GPU.

Nvidia and their partners had a number of cars and trucks on display throughout the show, showcasing various pieces of technology that are being developed to aid in the pursuit of autonomous vehicles.

Also on display in the category of “actually graphics related” was the new Max-Q version of the mobile Quadro P4000, which is integrated into PNY’s first mobile workstation, the Prevail Pro. Besides supporting professional VR applications, the HDMI and dual DisplayPort outputs allow a total of three external displays up to 4K each. It isn’t the smallest or lightest 15-inch laptop, but it is the only system under 17 inches I am aware of that supports the P4000, which is considered the minimum spec for professional VR implementation.

There are, of course, lots of other vendors exhibiting their products at GTC. I had the opportunity to watch 8K stereo 360 video playing off of a laptop with an external GPU. I also tried out the VRHero 5K Plus enterprise-level HMD, which brings the VR experience to whole other level. Much more affordable is TP-Cast’s $300 wireless upgrade Vive and Rift HMDs, the first of many untethered VR solutions. HTC has also recently announced the Vive Pro, which will be available in April for $800. It increases the resolution by 1/3 in both dimensions to 2880×1600 total, and moves from HDMI to DisplayPort 1.2 and USB-C. Besides VR products, they also had all sorts of robots in various forms on display.

Clearly the world of GPUs has extended far beyond the scope of accelerating computer graphics generation, and Nvidia is leading the way in bringing massive information processing to a variety of new and innovative applications. And if that leads us to hardware that can someday raytrace in realtime at 8K in VR, then I suppose everyone wins.


Mike McCarthy is an online editor/workflow consultant with 10 years of experience on feature films and commercials. He has been involved in pioneering new solutions for tapeless workflows, DSLR filmmaking and multi-screen and surround video experiences. Check out his site.


One thought on “GTC embraces machine learning and AI

  1. Anna Taylor

    Hey. thanks for sharing this valuable resource with us. I have a question in my mind. That is “What is the distinction between AI, Machine Learning, NLP, and Deep Learning?” I hope you will cover it in your next post.

    Reply

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