Category: Nvidia
Nvidia Press Conference at Computex 2018
Jensen Huang, Founder and CEO of Nvidia, Announces Jetson Xavier which I have filmed a separate interview about here, he does not launch the rumored GTX2080 or GTX1180 next-gen graphics cards yet, provides update on Max-Q thinner full GPU gaming laptops, talks DGX-2 supercomputer "The World's Largest GPU" (an update on the DGX which I filmed here) with 2 petaflops of performance in one node, 512GB frame buffer which has set 5 world records: fastest single chip, fastest single node, fastest at scale, fastest inference, and highest inference throughput.
$1299 Nvidia Jetson Xavier dev kit, 8-core ARMv8, 512-core Volta GPU for AI Robotics
Nvidia launes Jetson Xavier with 20x the performance of Jetson TX2 and 10x the energy efficiency with 512-core Volta GPU with Tensor Cores in an embedded module with more than 9 billion transistors it runs at under 30W, with multiple operating modes at 10W, 15W, and 30W. The Jetson Xavier ARM SoC has 6 kinds of high-performance processors on its SoC, a Volta Tensor Core GPU, an eight-core ARM64 CPU, dual NVDLA deep learning accelerators, an image processor, a vision processor and a video processor. Jetson Xavier has a peak performance of up to 30 TOPS (trillion operations per second) of mixed-precision FP32/FP16/INT8 performance. It can encode dual 4K60 H265 and decode dual 4K60 H265 at up to 12bit. Comes with 16GB LPDDR4x RAM with 137GB/s memory bandwidth, 32GB eMMC storage. It also has a dual NVDLA DL/ML Accelerator Engines which are open source available at http://nvdla.org and a 7-way VLIW Vision Accelerator. Nvidia Jetson Xavier runs using the Nvidia Isaac platform, a toolbox for the simulation, training, verification and deployment of Jetson Xavier. This robotics software consists of: Isaac SDK, APIs and tools to develop robotics algorithm software and runtime framework with fully accelerated libraries, Isaac IMX (Intelligent Machine Acceleration) applications, a collection of NVIDIA-developed robotics algorithm software, Isaac Sim, a highly realistic virtual simulation environment for developers to train autonomous machines and perform hardware-in-the-loop testing with Jetson Xavier. The Nvidia Jetson Xavier developer kit, which includes the Isaac robotics software, will be priced at $1,299, with early access starting in August from distributors worldwide.
IBM Supercomputer on Power9 and Nvidia GPU
Using IBM Power9 and Nvidia Volta GPU technology, the Summit system is a proven AI pioneer expected to deliver in excess of 200 Peta flops of performance, likely making it one of the world’s most powerful supercomputer.
Blade Shadow cloud gaming pc service launched in UK and California
Here I film at the UK launch of the Blade Shadow cloud PC gaming service, at the Meltdown London e-sports bar, where they have setup a bunch of Shadow PCs for cloud based gaming PC streaming service
here powering their League of Legends tournament. Blade Shadow is a French startup who I also interviewed at CES here they have now launched their service to cover the UK and they have also activated their West Coast USA server to serve customers in California. For about $35 per month you get remote access to "your own" Xeon gaming desktop with an Nvidia GTX1080 GPU, 12GB RAM, 256GB SSD running Windows 10 Pro.
Shadow Blade cloud PC Xeon/GTX1080 for cloud gaming, cloud 4K60/8K video-editing
French startup Blade presents their awesome Shadow cloud PC service at €30/month that streams a very powerful $2000 (equivalent) desktop PC hosted on their server powered by a high-end 8-threaded Intel Xeon server CPU with an Nvidia GTX1080 GPU, 12GB RAM, 256GB SSD (with harddrive/SSD storage expansion options available) running a full Windows 10 Pro desktop remotely in their server, using low-lag Internet technologies that they have developed, fast codecs (to have at least 15mbit/s Internet bandwidth available is recommended for a good experience), fast tricks that they have developed to make this all possible, to offer cloud gaming or high-end video-editing, 3D graphics rendering, audio processing, or anything else that might be useful to run on advanced PC hardware that you can think of, and you can then run that through client applications either running on their AMD APU based Shadow PC thin client that they offer to their subscribers (for a smooth up to 4K60 or 1080p144hz gaming experience), or you can run clients on a Chromebook, any Android phone, Android TV, Macbooks, any Windows machine, Linux, iPhone, iPad, their service runs on everything. Currently their service works well in France, initially it was just for French users who had Fiber to the home connections, but now it also runs smoothly onto any ADSL, Cable even LTE devices in France, the service is also supported in Belgium and a few other countries nearby France. Because for a good service, the user has to be within as few hops in the global backbone internet network as possible, to experience as little lag times as possible. Advanced professional gamers have tested this system and they have reported that they cannot feel any difference between the Shadow cloud gaming service and a local desktop gaming machine. The lag time are said to depend more on the speed of the PC monitor than of the internet back to their cloud server system. They are about to expand their offering to cover the whole of California as they are setting up a cloud server system right now in the Silicon Valley also. They plan to expand their services globally in the near future according to demand.
Nvidia DGX Station, world’s most powerful desktop, a Supercomputer at the office
Nvidia DGX Station is the world’s first and fastest personal supercomputer for leading-edge AI development at Supercomputing developers desk, it has the computing capacity of four server racks in a desk-friendly package, using less than one twentieth the power. It’s the only personal supercomputer with four Nvidia Tesla V100 GPUs, next generation Nvidia NVLink, and new Tensor Core architecture. DGX Station delivers 3X the training performance of today’s fastest workstations, with 480 TFLOPS of water cooled performance (3X Faster Than the Fastest Workstations) and FP16 precision. It's designed to be whisper quiet at one tenth the noise of other deep learning workstations, it’s designed for easy experimentation at the office.
Filmed in 4K60 at Supercomputing 2017 in Denver using Panasonic GH5 ($1999 at Amazon.com) on firmware 2.1 (aperture priority, AF continuous tracking) with Leica 12mm f1.4 ($1297 at Amazon.com) with Sennheiser MKE440 stereo shotgun microphone ($325 at Amazon.com), get $25 off renting cameras and lenses with my referral link at https://share.lensrentals.com/x/wWbHqV
Nvidia DRIVE PX Pegasus board for self-driving cars has 2 Octa-core ARM SoCs with 512-core CUDA GPU and 2 discreet GPUs for a total of 320 Billion calculations per second
Nvidia DRIVE PX Pegasus board is launched for self-driving cars which includes two ARM SoCs each feature Octa-core Nvidia Xavier Custom ARM processors with Volta 512-core CUDA GPU which supports up to 8K video encode and decode, 7Billion transistors each ARM SoC built on TSMC 16nm FinFET+ with also two next-generation discrete GPUs separately on the board with hardware created for accelerating deep learning and computer vision algorithms, the 4 chips on the board can compute 320 Billion calculations per second with an overall 1TB per second memory bandwidth.
Read more:
http://www.marketwired.com/press-release/nvidia-announces-worlds-first-ai-computer-to-make-robotaxis-a-reality-nasdaq-nvda-2236493.htm
https://www.nvidia.com/en-us/self-driving-cars/drive-px/
https://arstechnica.com/cars/2017/10/nvidias-drive-px-pegasus-is-its-newest-self-driving-supercomputer/
https://www.theverge.com/2017/10/10/16449416/nvidia-pegasus-self-driving-car-ai-robotaxi
https://www.engadget.com/2017/10/10/nvidia-introduces-a-computer-for-level-5-autonomous-cars/
