Tag Archives: GTC Conference

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.

What was new at GTC 2017

By Mike McCarthy

I, once again, had the opportunity to attend Nvidia’s GPU Technology Conference (GTC) in San Jose last week. The event has become much more focused on AI supercomputing and deep learning as those industries mature, but there was also a concentration on VR for those of us from the visual world.

The big news was that Nvidia released the details of its next-generation GPU architecture, code named Volta. The flagship chip will be the Tesla V100 with 5,120 CUDA cores and 15 Teraflops of computing power. It is a huge 815mm chip, created with a 12nm manufacturing process for better energy efficiency. Most of its unique architectural improvements are focused on AI and deep learning with specialized execution units for Tensor calculations, which are foundational to those processes.

Tesla V100

Similar to last year’s GP100, the new Volta chip will initially be available in Nvidia’s SXM2 form factor for dedicated GPU servers like their DGX1, which uses the NVLink bus, now running at 300GB/s. The new GPUs will be a direct swap-in replacement for the current Pascal based GP100 chips. There will also be a 150W version of the chip on a PCIe card similar to their existing Tesla lineup, but only requiring a single half-length slot.

Assuming that Nvidia puts similar processing cores into their next generation of graphics cards, we should be looking at a 33% increase in maximum performance at the top end. The intermediate stages are more difficult to predict, since that depends on how they choose to tier their cards. But the increased efficiency should allow more significant increases in performance for laptops, within existing thermal limitations.

Nvidia is continuing its pursuit of GPU-enabled autonomous cars with its DrivePX2 and Xavier systems for vehicles. The newest version will have a 512 Core Volta GPU and a dedicated deep learning accelerator chip that they are going to open source for other devices. They are targeting larger vehicles now, specifically in the trucking industry this year, with an AI-enabled semi-truck in their booth.

They also had a tractor showing off Blue River’s AI-enabled spraying rig, targeting individual plants for fertilizer or herbicide. It seems like farm equipment would be an optimal place to implement autonomous driving, allowing perfectly straight rows and smooth grades, all in a flat controlled environment with few pedestrians or other dynamic obstructions to be concerned about (think Interstellar). But I didn’t see any reference to them looking in that direction, even with a giant tractor in their AI booth.

On the software and application front, software company SAP showed an interesting implementation of deep learning that analyzes broadcast footage and other content looking to identify logos and branding, in order to provide quantifiable measurements of the effectiveness of various forms of brand advertising. I expect we will continue to see more machine learning implementations of video analysis, for things like automated captioning and descriptive video tracks, as AI becomes more mature.

Nvidia also released an “AI-enabled” version of I-Ray to use image prediction to increase the speed of interactive ray tracing renders. I am hopeful that similar technology could be used to effectively increase the resolution of video footage as well. Basically, a computer sees a low-res image of a car and says, “I know what that car should look like,” and fills in the rest of the visual data. The possibilities are pretty incredible, especially in regard to VFX.

Iray AI

On the VR front, Nvidia announced a new SDK that allows live GPU-accelerated image stitching for stereoscopic VR processing and streaming. It scales from HD to 5K output, splitting the workload across one to four GPUs. The stereoscopic version is doing much more than basic stitching, processing for depth information and using that to filter the output to remove visual anomalies and improve the perception of depth. The output was much cleaner than any other live solution I have seen.

I also got to try my first VR experience recorded with a Light Field camera. This not only gives the user a 360 stereo look around capability, but also the ability to move their head around to shift their perspective within a limited range (based on the size the recording array). The project they were using to demo the technology didn’t highlight the amazing results until the very end of the piece, but when it did that was the most impressive VR implementation I have had the opportunity to experience yet.
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Mike McCarthy is an online editor/workflow consultant with 10 years of experience on feature films and commercials. He has been working on new solutions for tapeless workflows, DSLR filmmaking and multi-screen and surround video experiences. Check out his site.

Nvidia’s GPU Technology Conference: Part II

By Fred Ruckel

A couple of weeks ago I had the pleasure of attending Nvidia’s GPU Technology Conference in San Jose. I spent five days sitting in on conferences, demos, and in a handful of one-on-one meetings. If the Part I of my story had you interested in the new world of GPU technology, take a dive into this installment and learn what other cool things Nvidia has created to enhance your workflow.

Advanced Rendering Solutions
We consider rendering to be the final output of an animation. While that’s true, there’s a lot
more to rendering than just the final animated result. We could jump straight to the previz Continue reading