DOCSLIB.ORG

Jen-Hsun Huang, Co-Founder & Ceo, Nvidia | Gtc China 2016

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Jen-Hsun Huang, Co-Founder & Ceo, Nvidia | Gtc China 2016 THE DEEP LEARNING AI REVOLUTION JEN-HSUN HUANG, CO-FOUNDER & CEO, NVIDIA | GTC CHINA 2016 GPU DEEP LEARNING BIG BANG ImageNet Classification with Deep Convolutional Neural Networks Alex Krizhevsky Ilya Sutskever Geoffrey e. Hinton University of Toronto University of Toronto University of Toronto NIPS (2012) Deep Learning NVIDIA GPU GPU DEEP LEARNING ACHIEVES “SUPERHUMAN” RESULTS ImageNet — Accuracy % 96% Human Microsoft, Google 3.5% error rate DL 74% Hand-coded CV 2010 2011 2012 2013 2014 2015 2012: Deep Learning researchers 2015: DNN achieves superhuman 2015: Deep Speech 2 achieves worldwide discover GPUs image recognition superhuman voice recognition NVIDIA — “THE AI COMPUTING COMPANY” GPU Computing Computer Graphics Artificial Intelligence ANNOUNCING NEW GRAPHICS SDKS Ansel Volumetric OptiX 4.0 Mental Ray MDL 1.0 In-game Photography Physical Light Models Multi-GPU Ray-Tracing Now GPU-Accelerated! Physically Based Materials Funhouse VR 360 Video 1.0 Iray VR Remote Rendering GVDB Open Source Real-Time Panoramic VR Photorealistic VR Ray Tracing Video Compositing Sparse Volumes for Special Effects NVIDIA VR FUNHOUSE NVIDIA SILICON VALLEY HEADQUARTERS GTC — 25X GROWTH IN GPU DL DEVELOPERS s 16,000 400,000 55,000 • Higher Ed 35% • Australia • Software 19% • China • Internet 15% • Europe • Auto 10% • India 120,000 • Government 5% • Japan • Medical 4% • Japan 3,700 • Korea 2,200 • Finance 4% • United States • United States • Manufacturing 4% (Silicon Valley, D.C.) 2014 2016 2014 2016 2014 2016 4X Attendees 3X GPU Developers 25x Deep Learning Developers WHY DID AI RESEARCHERS ADOPT GPUs FOR DEEP LEARNING? BRAIN IS LIKE A GPU ?? BRAIN CREATES MENTAL IMAGES WHEN WE THINK GPU IS LIKE A BRAIN GPU DEEP LEARNING IS A NEW COMPUTING MODEL Training Datacenter Device GPU DEEP LEARNING IS A NEW COMPUTING MODEL Billions of Trillions of Operations GPU train larger models, accelerate time to market Training Datacenter TRAINING Device GPU DEEP LEARNING IS A NEW COMPUTING MODEL 10s of billions of image, voice, video queries per day Training Datacenter GPU inference for fast response, maximize datacenter throughput DATACENTER INFERENCING Device GPU DEEP LEARNING IS A NEW COMPUTING MODEL Training Datacenter Billions of intelligent devices GPU for real-time accurate response Device DEVICE INFERENCING AI — THE ULTIMATE COMPUTING CHALLENGE IMAGE RECOGNITION SPEECH RECOGNITION Important Property of Neural Networks 20 ExaFLOPS Results get better with 16X 10X Model 152 layers Training Ops 22.6 GFLOP/image 100M | 12,000 Hours more data + ~3.5% error ~5% Error bigger models + 8 layers 2 ExaFLOPS 1.4 GFLOP/image more computation ~16% Error 25M | 7,000 Hours ~8% Error (Better algorithms, new insights and 2012 2015 2014 2015 improved techniques always help, too!) AlexNet ResNet Deep Speech 1 Deep Speech 2 PASCAL “5 MIRACLES” BOOST DEEP LEARNING 65X 70X Pascal 60X 50X 40X 30X PaddlePaddle 20X Baidu Deep Learning Maxwell 10X Kepler X 2013 2014 2015 2016 Pascal 16nm FinFET CoWoS HBM2 NVLink cuDNN Pascal — 5 Miracles NVIDIA DGX-1 Supercomputer 65X in 4 yrs Accelerate Every Framework Chart: Relative speed-up of images/sec vs K40 in 2013. AlexNet training throughput based on 20 iterations. CPU: 1x E5-2680v3 12 Core 2.5GHz. 128GB System Memory, Ubuntu 14.04. M40 datapoint: 8x M40 GPUs in a node P100: 8x P100 NVLink-enabled. ANNOUNCING NEW IBM SERVER POWER8 + NVIDIA TESLA P100 FOR THE AI ENTERPRISE “Putting NVIDIA’s technology into the IBM system will speed up performance for such emerging workloads as AI, deep learning and data analytics.” — eWeek Andrew Ng, Chief Scientist Training Datacenter Device ANNOUNCING TESLA P4 & P40 INFERENCING ACCELERATORS Pascal Architecture | INT8 P40: 250W | 40X Energy Efficient versus CPU P40: 250W | 40X Performance versus CPU ANNOUNCING TensorRT PERFORMANCE OPTIMIZING INFERENCING ENGINE FP32, FP16, INT8 | Vertical & Horizontal Fusion | Auto-Tuning VGG, GoogLeNet, ResNet, AlexNet & Custom Layers Available Today: developer.nvidia.com/tensorrt Alibaba/Aliyun Amazon Baidu eBay Facebook Flickr Google iFLYTEK NVIDIA GPU DEEP LEARNING iQIYI JD.com Microsoft Netflix Orange Periscope Pinterest Qihoo 360 EVERYWHERE Shazam Skype Sogou Tencent Twitter Yahoo Supermarket Yandex Yelp >1,500 AI STARTUPS AROUND THE WORLD Deep Learning for Cybersecurity Deep Learning for Genomics Deep Learning for Self-Driving Cars Deep Learning for Art AI STARTUPS IN CHINA Weather & Environment Eye-tracking for Human- Medical Face Product Recognition, Personal Forecast machine Interaction Imaging Recognition Detection, Search Concierge App Training Datacenter Device “BILLIONS OF INTELLIGENT DEVICES” “Billions of intelligent devices will take advantage of DNNs to provide personalization and localization as GPUs become faster and faster over the next several years.” — Tractica AI CITY — 1B CAMERAS BY 2020 ~1 billion cameras worldwide by 2020 30 billion inferences/sec Tesla P40: 2,500 inferences/sec @ 720P AI City needs ~10M P40 servers DATA: 1B cameras, IHS “Video Surveillance Intelligence Service, Aug. 2016” 1/20TH THE SPACE, 1/10TH THE POWER ~21 1U Servers 42 CPUs ~4,000 W 1 Hikvision Blade 16 TX1 + 1 CPU >8 1080 streams ~300 W Traditional Server Hikvision Blade NVIDIA DGX-1 Hikvision Blade 16 Jetson TX1s ANNOUNCING NVIDIA AI CITY PARTNERS AI TRANSPORTATION — $10T INDUSTRY PERCEPTION AI PERCEPTION AI LOCALIZATION DRIVING AI DEEP LEARNING FREE SPACE DETECTION CAR 3D DETECTION NVIDIA BB8 AI CAR NVIDIA DRIVE PX 2 AUTOCRUISE TO FULL AUTONOMY Full Autonomy ONE ARCHITECTURE AUTONOMOUS DRIVING AutoChauffeur Perception, Reasoning, Driving AI Supercomputing, AI Algorithms, Software AutoCruise Scalable Architecture NVIDIA DRIVE PX 2 AUTOCRUISE 10W AI Car Computer | Passive Cooling | Automotive IO AI Highway Driving | Localization & Mapping NVIDIA & BAIDU PARTNER ON AI SELF-DRIVING CARS NVIDIA AI SELF-DRIVING CARS IN DEVELOPMENT Baidu nuTonomy Volvo WEpods NVIDIA NVIDIA END-TO-END DEEP LEARNING PLATFORM PaddlePaddle Baidu Deep Learning TESLA P100 DGX-1 TRAINING NVIDIA END-TO-END DEEP LEARNING PLATFORM PaddlePaddle Baidu Deep Learning ANNOUNCING TensorRT TESLA P100 DGX-1 ANNOUNCING TESLA P4 & P40 TRAINING DATACENTER INFERENCING NVIDIA END-TO-END DEEP LEARNING PLATFORM CUDA PaddlePaddle JETPACK DRIVEWORKS Baidu Deep Learning ANNOUNCING TensorRT ANNOUNCING TESLA P100 DGX-1 ANNOUNCING TESLA P4 & P40 JETSON TX1 DRIVE PX 2 AUTOCRUISE TRAINING DATACENTER INFERENCING INTELLIGENT DEVICES NVIDIA DEEP LEARNING PLATFORM PARTNERS AI ENTERPRISE AI CITY AI CAR AI FOR EVERYONE AI will Revolutionize Transportation AI will Revolutionize Healthcare AI will Revolutionize Society .
Load more

Recommended publications
  • Realityserver Installation Guide
    RealityServer Êc Web Services 3.1 Installation Guide Document version 1.28 December 8, 2010 Installation Guide Copyright Information c 1986, 2011 NVIDIA Corporation. All rights reserved. This document is protected under copyright law. The contents of this document may not be translated, copied or duplicated in any form, in whole or in part, without the express written permission of NVIDIA Corporation. The information contained in this document is subject to change without notice. NVIDIA Corporation and its employees shall not be responsible for incidental or consequential damages resulting from the use of this material or liable for technical or editorial omissions made herein. NVIDIA, the NVIDIA logo, and DiCE, imatter, iray, mental cloud, mental images, mental matter, mental mesh, mental mill, mental queue, mental ray, Metanode, MetaSL, neuray, Phenomenon, RealityDesigner, RealityPlayer, RealityServer, rendering imagination visible, Shape-By-Shading, and SPM, are trademarks and/or registered trademarks of NVIDIA Corporation. Other product names mentioned in this document may be trademarks or registered trademarks of their respective companies and are hereby acknowledged. Installation, doc. 1.28 c 1986, 2011 NVIDIA Corporation. Table of Contents Table of Contents System Requirements 1 Memory 1 Processors 1 Graphics Card 1 Operating System 4 Network 4 RealityServer Web Services Installation 5 Firewalls 5 Network Buffers 5 Software Protection Manager (SPM) 5 RealityServer Web Services Networking Setup 6 Network Setup 6 c 1986,2011NVIDIACorporation. Installation,doc. 1.28 i Table of Contents ii Installation, doc. 1.28 c 1986, 2011 NVIDIA Corporation. System Requirements— Graphics Card System Requirements Memory Memory requirements greatly depend on the size of the 3D scene, and the number of different scenes concurrently loaded.
    [Show full text]
  • The Growing Importance of Ray Tracing Due to Gpus
    NVIDIA Application Acceleration Engines advancing interactive realism & development speed July 2010 NVIDIA Application Acceleration Engines A family of highly optimized software modules, enabling software developers to supercharge applications with high performance capabilities that exploit NVIDIA GPUs. Easy to acquire, license and deploy (most being free) Valuable features and superior performance can be quickly added App’s stay pace with GPU advancements (via API abstraction) NVIDIA Application Acceleration Engines PhysX physics & dynamics engine breathing life into real-time 3D; Apex enabling 3D animators CgFX programmable shading engine enhancing realism across platforms and hardware SceniX scene management engine the basis of a real-time 3D system CompleX scene scaling engine giving a broader/faster view on massive data OptiX ray tracing engine making ray tracing ultra fast to execute and develop iray physically correct, photorealistic renderer, from mental images making photorealism easy to add and produce © 2010 Application Acceleration Engines PhysX • Streamlines the adoption of latest GPU capabilities, physics & dynamics getting cutting-edge features into applications ASAP, CgFX exploiting the full power of larger and multiple GPUs programmable shading • Gaining adoption by key ISVs in major markets: SceniX scene • Oil & Gas Statoil, Open Inventor management • Design Autodesk, Dassault Systems CompleX • Styling Autodesk, Bunkspeed, RTT, ICIDO scene scaling • Digital Content Creation Autodesk OptiX ray tracing • Medical Imaging N.I.H iray photoreal rendering © 2010 Accelerating Application Development App Example: Auto Styling App Example: Seismic Interpretation 1. Establish the Scene 1. Establish the Scene = SceniX = SceniX 2. Maximize interactive 2. Maximize data visualization quality + quad buffered stereo + CgFX + OptiX + volume rendering + ambient occlusion 3.
    [Show full text]
  • GPU Based Cloud Computing
    GPU based cloud computing Dairsie Latimer, Petapath, UK Petapath © NVIDIA Corporation 2010 About Petapath Petapath ! " Founded in 2008 to focus on delivering innovative hardware and software solutions into the high performance computing (HPC) markets ! " Partnered with HP and SGI to deliverer two Petascale prototype systems as part of the PRACE WP8 programme ! " The system is a testbed for new ideas in usability, scalability and efficiency of large computer installations ! " Active in exploiting emerging standards for acceleration technologies and are members of Khronos group and sit on the OpenCL working committee ! " We also provide consulting expertise for companies wishing to explore the advantages offered by heterogeneous systems © NVIDIA Corporation 2010 What is Heterogeneous or GPU Computing? x86 PCIe bus GPU Computing with CPU + GPU Heterogeneous Computing © NVIDIA Corporation 2010 Low Latency or High Throughput? CPU GPU ! " Optimised for low-latency ! " Optimised for data-parallel, access to cached data sets throughput computation ! " Control logic for out-of-order ! " Architecture tolerant of and speculative execution memory latency ! " More transistors dedicated to computation © NVIDIA Corporation 2010 NVIDIA GPU Computing Ecosystem ISV CUDA CUDA TPP / OEM Training Development Company Specialist Hardware GPU Architecture Architect VAR CUDA SDK & Tools Customer Application Customer NVIDIA Hardware Requirements Solutions Hardware Architecture © NVIDIA Corporation 2010 Deployment Science is Desperate for Throughput Gigaflops 1,000,000,000
    [Show full text]
  • Nvidia Corporation 2016 Annual Report
    2017 NVIDIA CORPORATION ANNUAL REVIEW NOTICE OF ANNUAL MEETING PROXY STATEMENT FORM 10-K THE AGE OF THE GPU IS UPON US THE NEXT PLATFORM A decade ago, we set out to transform the GPU into a powerful computing platform—a specialized tool for the da Vincis and Einsteins of our time. GPU computing has since opened a floodgate of innovation. From gaming and VR to AI and self-driving cars, we’re at the center of the most promising trends in our lifetime. The world has taken notice. Jensen Huang CEO and Founder, NVIDIA NVIDIA GEFORCE HAS MOVED FROM GRAPHICS CARD TO GAMING PLATFORM FORBES The PC drives the growth of computer gaming, the largest entertainment industry in the world. The mass popularity of eSports, the evolution of gaming into a social medium, and the advance of new technologies like 4K, HDR, and VR will fuel its further growth. Today, 200 million gamers play on GeForce, the world’s largest gaming platform. Our breakthrough NVIDIA Pascal architecture delighted gamers, and we built on its foundation with new capabilities, like NVIDIA Ansel, the most advanced in-game photography system ever built. To serve the 1 billion new or infrequent gamers whose PCs are not ready for today’s games, we brought the GeForce NOW game streaming service to Macs and PCs. Mass Effect: Andromeda. Courtesy of Electronic Arts. THE BEST ANDROID TV DEVICE JUST GOT BETTER ENGADGET NVIDIA SHIELD TV, controller, and remote. NVIDIA SHIELD is taking NVIDIA gaming and AI into living rooms around the world. The most advanced streamer now boasts 1,000 games, has the largest open catalog of media in 4K, and can serve as the brain of the AI home.
    [Show full text]
  • Form 10-K Nvidia Corporation
    Table of Contents UNITED STATES SECURITIES AND EXCHANGE COMMISSION Washington, D.C. 20549 ____________________________________________________________________________________________ FORM 10-K [x] ANNUAL REPORT PURSUANT TO SECTION 13 OR 15(d) OF THE SECURITIES EXCHANGE ACT OF 1934 For the fiscal year ended January 28, 2018 OR [_] TRANSITION REPORT PURSUANT TO SECTION 13 OR 15(d) OF THE SECURITIES EXCHANGE ACT OF 1934 Commission file number: 0-23985 NVIDIA CORPORATION (Exact name of registrant as specified in its charter) Delaware 94-3177549 (State or other jurisdiction of (I.R.S. Employer Incorporation or Organization) Identification No.) 2788 San Tomas Expressway Santa Clara, California 95051 (408) 486-2000 (Address, including zip code, and telephone number, including area code, of principal executive offices) Securities registered pursuant to Section 12(b) of the Act: Title of each class Name of each exchange on which registered Common Stock, $0.001 par value per share The NASDAQ Global Select Market Securities registered pursuant to Section 12(g) of the Act: None Indicate by check mark if the registrant is a well-known seasoned issuer, as defined in Rule 405 of the Securities Act. Yes ý No o Indicate by check mark if the registrant is not required to file reports pursuant to Section 13 or Section 15(d) of the Act. Yes o No ý Indicate by check mark whether the registrant (1) has filed all reports required to be filed by Section 13 or 15(d) of the Securities Exchange Act of 1934 during the preceding 12 months (or for such shorter period that the registrant was required to file such reports), and (2) has been subject to such filing requirements for the past 90 days.
    [Show full text]
  • NVIDIA Quadro VCA Manager User's and Administrator's Guide
    NVIDIA Quadro VCA Manager User's and administrator's guide NVIDIA Advanced Rendering Center Fasanenstraße 81 10623 Berlin Germany phone +49.30.315.99.70 fax +49.30.315.99.733 arc-offi[email protected] Copyright Information © 1986, 2015 NVIDIA ARC GmbH. All rights reserved. This document is protected under copyright law. The contents of this document may not be translated, copied or duplicated in any form, in whole or in part, without the express written permission of NVIDIA ARC GmbH. The information contained in this document is subject to change without notice. NVIDIA ARC GmbH and its employees shall not be responsible for incidental or consequential damages resulting from the use of this material or liable for technical or editorial omissions made herein. NVIDIA and the NVIDIA logo are registered trademarks of NVIDIA Corporation. imatter, IndeX, Iray, mental images, mental ray, and RealityServer are trademarks and/or registered trademarks of NVIDIA ARC GmbH. Other product names mentioned in this document may be trademarks or registered trademarks of their respective companies and are hereby ac- knowledged. Document build number 240329 ii VCA Manager Guide ©1986,2015 NVIDIA ARC GmbH Contents 1 Introduction to VCA Manager......................................... 1 2 Connecting to VCA Manager.......................................... 1 3 Logging in to VCA Manager.......................................... 2 3.1 VCA Manager Login window: Overview............................. 2 3.2 Logging in to VCA Manager: Procedure.............................. 2 4 Reserving VCAs.................................................... 3 4.1 VCA Manager Overview window: Overview.......................... 3 4.1.1 User status.................................................. 4 4.1.2 My Visual Computing Cluster.................................. 5 4.1.3 Visual Computing Appliance Pool............................... 7 4.1.4 Messages..................................................
    [Show full text]
  • 2018 Nvidia Corporation Annual Review
    2018 NVIDIA CORPORATION ANNUAL REVIEW NOTICE OF ANNUAL MEETING PROXY STATEMENT FORM 10-K GPUS ARE POWERING SOME OF THE HOTTEST TRENDS NOW AND FOR DECADES TO COME. YAHOO FINANCE Scientists using GPU computing were able to “see” gravitational waves for the first time in human history. Twenty-five years ago, we set out to transform computer graphics. Fueled by the massive growth of the gaming market and its insatiable demand for better 3D graphics, we’ve evolved the GPU into a computer brain at the intersection of virtual reality, high performance computing, and artificial intelligence. NVIDIA GPU computing has become the essential tool of the da Vincis and Einsteins of our time. For them, we’ve built the equivalent of a time machine. Jensen Huang CEO and Founder, NVIDIA Hellblade: Senua’s Sacrifice, as captured by NVIDIA Ansel, a powerful in-game camera that lets users take professional- grade photographs of their games. NVIDIA GEFORCE HAS MOVED FROM GRAPHICS CARD TO GAMING PLATFORM. FORBES At $100 billion, computer gaming is the world’s largest entertainment industry. And with 200 million gamers, NVIDIA GeForce is its largest platform. We continuously innovate across the GeForce platform, from GeForce GTX GPUs to GeForce Experience, and in new technologies like Max-Q that make gaming laptops thinner, quieter and faster. And we’re opening high-end gaming and blockbuster titles to millions of users for the first time with NVIDIA GeForce NOW, a cloud-based service that turns everyday PC and Mac laptops into virtual GeForce gaming machines. NVIDIA’S LATEST TECH IS HERE TO BLOW POSSIBILITIES OF VR WIDE OPEN.
    [Show full text]
  • View Annual Report
    ar5182 Electronic EDGAR Proof Job Number: -NOT DEFINED- Filer: -NOT DEFINED- Form Type: 10-K Reporting Period / Event Date: 01/25/09 Customer Service Representative: -NOT DEFINED- Revision Number: -NOT DEFINED- This proof may not fit on letter-sized (8.5 x 11 inch) paper. If copy is cut off, please print to a larger format, e.g., legal- sized (8.5 x 14 inch) paper or oversized (11 x 17 inch) paper. Accuracy of proof is guaranteed ONLY if printed to a PostScript printer using the correct PostScript driver for that printer make and model. (this header is not part of the document) EDGAR Submission Header Summary Submission Type 10-K Live File on Return Copy on Submission Contact Aarti Ratnam Submission Contact Phone Number 408-566-5163 Exchange NASD Confirming Copy off Filer CIK 0001045810 Filer CCC xxxxxxxx Period of Report 01/25/09 Smaller Reporting Company off Shell Company No Voluntary Filer No Well-Known Seasoned Issuer Yes Notify via Filing website Only off Emails [email protected] Documents 10-K fy2009form10k.htm FISCAL YEAR 2009 FORM 10-K EX-21.1 fy2009subsidiaries.htm LISTING OF SUBSIDIARIES EX-23.1 fy2009pwcconsent.htm CONSENT OF INDEPENDENT REGISTERED PUBLIC ACCOUNTING FIRM EX-31.1 fy2009cert302ceo.htm 302 CERTIFICATION OF CEO EX-31.2 fy2009cert302cfo.htm 302 CERTIFICATION OF CFO EX-32.1 fy2009906certceo.htm 906 CERTIFICATION OF CEO EX-32.2 fy2009906certcfo.htm 906 CERTIFICATION OF CFO GRAPHIC fiveyearsperfstockgraph.jpg FIVE YEARS STOCK PERFORMANCE GRAPH GRAPHIC tenyearsperfstockgraph.jpg TEN YEARS STOCK PERFORMANCE GRAPH Module
    [Show full text]
  • Ray Tracing Gems II Next Generation Real-Time Rendering with DXR, Vulkan, and Optix
    Ray Tracing Gems II Next Generation Real-Time Rendering with DXR, Vulkan, and OptiX Edited by Adam Marrs, Peter Shirley, and Ingo Wald Section Editors Per Christensen David Hart Thomas Müller Jacob Munkberg Angelo Pesce Josef Spjut Michael Vance Cem Yuksel Ray Tracing Gems II: Next Generation Real-Time Rendering with DXR, Vulkan, and OptiX Edited by Section Editors Adam Marrs Per Christensen Angelo Pesce Peter Shirley David Hart Josef Spjut Ingo Wald Thomas Müller Michael Vance Jacob Munkberg Cem Yuksel ISBN-13 (pbk): 978-1-4842-7184-1 ISBN-13 (electronic): 978-1-4842-7185-8 https://doi.org/10.1007/978-1-4842-7185-8 Copyright © 2021 by NVIDIA Trademarked names, logos, and images may appear in this book. Rather than use a trademark symbol with every occurrence of a trademarked name, logo, or image we use the names, logos, and images only in an editorial fashion and to the beneft of the trademark owner, with no intention of infringement of the trademark. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identifed as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. While the advice and information in this book are believed to be true and accurate at the date of publication, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein.
    [Show full text]
  • 2017 Nvidia Corporation Annual Review
    2017 NVIDIA CORPORATION ANNUAL REVIEW NOTICE OF ANNUAL MEETING PROXY STATEMENT FORM 10-K THE AGE OF THE GPU IS UPON US THE NEXT PLATFORM A decade ago, we set out to transform the GPU into a powerful computing platform—a specialized tool for the da Vincis and Einsteins of our time. GPU computing has since opened a floodgate of innovation. From gaming and VR to AI and self-driving cars, we’re at the center of the most promising trends in our lifetime. The world has taken notice. Jensen Huang CEO and Founder, NVIDIA NVIDIA GEFORCE HAS MOVED FROM GRAPHICS CARD TO GAMING PLATFORM FORBES The PC drives the growth of computer gaming, the largest entertainment industry in the world. The mass popularity of eSports, the evolution of gaming into a social medium, and the advance of new technologies like 4K, HDR, and VR will fuel its further growth. Today, 200 million gamers play on GeForce, the world’s largest gaming platform. Our breakthrough NVIDIA Pascal architecture delighted gamers, and we built on its foundation with new capabilities, like NVIDIA Ansel, the most advanced in-game photography system ever built. To serve the 1 billion new or infrequent gamers whose PCs are not ready for today’s games, we brought the GeForce NOW game streaming service to Macs and PCs. Mass Effect: Andromeda. Courtesy of Electronic Arts. THE BEST ANDROID TV DEVICE JUST GOT BETTER ENGADGET NVIDIA SHIELD TV, controller, and remote. NVIDIA SHIELD is taking NVIDIA gaming and AI into living rooms around the world. The most advanced streamer now boasts 1,000 games, has the largest open catalog of media in 4K, and can serve as the brain of the AI home.
    [Show full text]
  • Speech Communication: 1974
    DOCUMENT RESUME ED 102 624 CS 500 992 AUTHOR Kennicott, Patrick C., Ed. TITLE Bibliographic Annual in Speech Communication: 1974. Volume 5. INSTITUTION Speech Communication Association, New York, N.Y. PUB DATE 74 ROTE 307p.; For related documents see CS 500 993-997 AVAILABLE FROM Speech Communication Association, Statler Hilton Hotel, New York, New York 10001 ($8.00 member, $9.00 nonmember) EDRS PRICE MF-$0.76HC-$15.86 PLUS POSTAGE DESCRIPTORS *Annotated Bibliographies; Bibliographies; *Communication (Thought Transfer); Doctoral Theses; *Educational Research; Higher Education; *Sass Media; Research Tools; *Speech; Theater Arts ABSTRACT This annotated bibliography is an annual volume devoted to maintaining a record of graduate work in speech communication, providing abstracts of doctoral dissertations, and making subject area bibliographies available. The contents of this volume include "Studies in Sass Communication: A Selected Bibliography, 1973" by Roland C. Johnson and Kenneth J. Ksobiech; "Behavioral Studies in Communication, 1973: A Selected Bibliography" by 1aomas N. Steinfatt; "A Selected Bibliography of Rhetorical Studies, 1973" by Michael C. Leff; "A Selected Bibliography of Public Address, 1973w by Harold Mixon; "Bibliography of Studies iv. Oral Interpretation, 1973" by James We Carlsen; "A Bibliography of Theatrical Craftsmanship, 1973" by Christian Moe and Jay E. Raphael; "Abstracts of Doctoral Dissertations in the Field of Speech Communication, 1973" by Cal H. Logue; and "Graduate Theses and Dissertations in the Field of Speech Communication, 1973." Also included is an "Index to Academic Departments Reporting Masters Theses and Doctoral Dissertations," by Flora Lisa Miller. UM) U.S. DIIIPARTMINT Of HEALTH. IP 12 EDUCATION I WELFARE NATIONAL INSTITUTE OF EDUCATION THIS DOCUMENT HAS BEENREPRO DUCED EXACTLY AS RECEIVEDFROM THE PERSON OR ORGt.NIZATION ORIGIN 11111M111M1111.
    [Show full text]
  • Advanced Rendering Offerings
    SIGGRAPH 2011 Vancouver August 8th2011 Agenda 1. Overview of mental images integration 2. How this impacts what NVIDIA provides 3. Overview of our Advanced Rendering offerings 4. Roadmap for where each technology is going 5. Glimpse at what we’re building next Advanced Graphics Always at its Core Worldwide Leader in GPU Development & Professional Graphics Advanced Rendering Commitment 2007 Worldwide Leader in World Leader in Photorealistic Rendering GPU Development & for Companies wanting Integrated Solutions Professional Graphics Multiple A.R. Commitments 2007 – 2011 World Class Middleware for Developers to Exploit the GPU Application Acceleration Engines World Leader in Photorealistic Rendering for Companies wanting Integrated Solutions Worldwide Leader in DevTech: Pro Graphics & HPC GPU Development & World Class Development Assistance Professional Graphics for Companies to Exploit the GPU Consolidated A.R. Commitment Today Worldwide Leader in The “Center of Gravity” for GPU Development & Advanced Rendering and Professional Graphics Professional Graphics NVIDIA ARC: Integrating to Accelerate Disciplines in mental images are now combined with their NVIDIA counterparts to merge expertise for: Ray Traced Rendering NV Research, OptiX mental ray, iray GPU computing OptiX, CUDA, HPC, etc iray, New Rendering Raster Rendering OpenGL, Cg, Tegra Interactive Rendering Scene Graphs SceniX Renderer Architectures Remoting Monterey Cloud Rendering Application Integration DevTech Rendering Integration Partner Engagements Strategic Alliances Business Development The “mental images” name is respectively retired, with commercial contracts and copyrights now being with: NVIDIA ARC GmbH NVIDIA ARC: Composition +120 technical people worldwide , with Berlin as HQ Comprised of cross-functional teams: Rendering Dev. Steven Parker includes: mental ray, iray, new renderers, OptiX, HPC DevTech Core Dev.
    [Show full text]