GTC JAPAN 9 月 13-14 日  開催予定

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GTC のパワーを体験する

GTC Japan は、NVIDIA が主催する日本最大の GPU テクノロジ イベントです。

NVIDIA の GPU Technology Conference (GTC) は、コンピューティング分野で、最重要でかつ不可欠とされるトレーニング、貴重なインサイト、NVIDIA をはじめとする主要な組織の専門家とのネットワーキングをご提供する、特別な AI/ディープラーニング イベントです。  

自律走行車、スマート シティ、ヘルスケア、ビッグ データ、ハイ パフォーマンス コンピューティング (HPC)、VR 等あらゆる分野における最新のブレイクスルーをご覧ください。

Connect

CONNECT

NVIDIA をはじめとする各企業/教育機関のあらゆる分野のエキスパート達との交流

LEARN

LEARN

ハンズオン、セッション、ポスターを通じて、貴重な洞察力と実践的なトレーニングを提供

Discover

DISCOVER

GPU テクノロジがディープラーニングなどの重要な分野で生み出している驚くべきブレークスルーを体験

Innovate

INNOVATE

ベンチャーやスタートアップ企業による業界の常識を打ち砕くイノベーション

GTC 2018 スポンサー

GTC Japan で GPU コンピューティング業界でのリーダーとして自社の地位を固めたいとお考えの方は、今すぐご応募ください。貴社のニーズに最も合致し、ご希望の機会を手に入れられることができるスポンサーシップ パッケージをカスタマイズするお手伝いをいたします。

GTC 2018 会場アクセス

グランドプリンスホテル新高輪 国際館パミール

東京都港区高輪 3-13-1

JENSEN HUANG

JENSEN HUANG

NVIDIA, Founder and CEO

Opening Keynote

ABOUT THE SPEAKER: Jensen Huang co-founded NVIDIA in 1993 and has served since its inception as president, chief executive officer and a member of the board of directors. Under his leadership, NVIDIA invented the graphics processing unit (GPU) in 1999. Since then, it has consistently set new standards in visual computing with breathtaking, interactive graphics available on devices ranging from smartphones and tablets to notebooks and workstations. NVIDIA's expertise in programmable GPUs has led to breakthroughs in parallel processing that make supercomputing inexpensive and widely accessible. The company holds more than 7,000 U.S. patents granted or pending, including ones covering designs and insights fundamental to modern computing. Huang is a recipient of the Dr. Morris Chang Exemplary Leadership Award from the Global Semiconductor Association in recognition of his exceptional contributions to driving the development, innovation, growth and long-term opportunities of the fabless semiconductor industry. He has received the Daniel J. Epstein Engineering Management Award from the University of Southern California and an honorary doctorate from Oregon State University. He was named to the U.S. Immigrant Entrepreneur Hall of Fame when it was established in 2012. Prior to founding NVIDIA, Huang worked at LSI Logic and Advanced Micro Devices. He holds a BSEE degree from Oregon State University and an MSEE degree from Stanford University.

SHALINI DE MELLO

SHALINI DE MELLO

NVIDIA, Senior Research Scientist

Synthetic Facial Data for Training Deep Neural Networks

ABOUT THE SPEAKER: Shalini De Mello has been a senior research scientist at NVIDIA Research since 2013. Shalini's interests are in computer vision and machine learning technology for human-computer interaction and smart interfaces. Prior to joining NVIDIA Research, she worked as a senior computer vision engineer at NVIDIA. Her work includes NVIDIA's shipping products for head pose tracking, hand gesture recognition, face detection, video stabilization, and libraries for the development for computer vision applications on mobile platforms. She received doctoral and master's degrees in electrical and computer engineering from the University of Texas at Austin in 2008 and 2004, respectively.

MARK HARRIS

MARK HARRIS

NVIDIA, Chief Technologist GPU Computing

ABOUT THE SPEAKER: Mark Harris is chief technologist for GPU Computing Software at NVIDIA. Mark has 15 years of experience developing software for GPUs, ranging from graphics and games to physically based simulation, parallel algorithms, and high performance computing. Mark has been using GPUs for general-purpose computing since before they even supported floating point arithmetic. While a Ph.D. student at the University of North Carolina, he recognized this nascent trend and coined a name for it: GPGPU (general-purpose computing on graphics processing units), and started GPGPU.org to provide a forum for those working in the field to share and discuss their work.

WILL RAMEY

WILL RAMEY

NVIDIA, Director, Developer Programs

Deep Learning Demystified

ABOUT THE SPEAKER: Will Ramey is director of developer programs at NVIDIA. Since joining the company in 2003 he has served in a number of marketing and management roles, including several years as the first product manager for CUDA and NVIDIA's developer tools. Currently Will leads teams responsible for promoting the NVIDIA SDK, developer programs, and the Deep Learning Institute. Prior to joining NVIDIA, he managed an independent game studio and developed advanced technology for the entertainment industry as a product manager and software engineer. He holds a BA in computer science from Willamette University and completed the Japan Studies Program at Tokyo International University. Outside of work Will enjoys the outdoors, learning Spanish, and open water swimming. Follow @wramey on Twitter to keep up with Will online.

BRYAN CATANZARO

BRYAN CATANZARO

NVIDIA, VP of Applied Deep Learning Research

Deep Learning Applications in Text and Graphics at NVIDIA

ABOUT THE SPEAKER: Bryan Catanzaro is VP of Applied Deep Learning Research at NVIDIA, where he leads a team solving problems in fields ranging from video games to chip design using deep learning. Prior to his current role at NVIDIA, he worked at Baidu to create next generation systems for training and deploying end-to-end deep learning based speech recognition. Before that, he was a researcher at NVIDIA, where he wrote the research prototype and drove the creation of CUDNN, the low-level library now used by most AI researchers and deep learning frameworks to train neural networks. Bryan earned his PhD from Berkeley, where he built the Copperhead language and compiler, which allows Python programmers to use nested data parallel abstractions efficiently. He earned his MS and BS from Brigham Young University, where he worked on computer arithmetic for FPGAs.

H. CARTER EDWARDS

H. CARTER EDWARDS

SANDIA NATIONAL LABORATORIES, Principle Member Technical Staff

Kokkos' Task DAG Parallelism for C++ HPC Applications

ABOUT THE SPEAKER: H. Carter Edwards is the principal investigator and architect for the Kokkos project at Sandia National Laboratories. He has over three decades of experience in modeling and simulation software development and over two decades of experience in HPC, parallel processing, and C++ software development. For the last several years, his HPC focus has been on algorithms and programming models for thread-scalable and performance portable parallelism across next-generation platform node architectures. Carter has a B.S. and M.S. in aerospace engineering and a Ph.D. in computational mathematics. He also represents Sandia on the ISO C++ language standard committee.

STEPHEN JONES

STEPHEN JONES

NVIDIA, Software & Systems Architect

CUDA [Version] and Beyond

ABOUT THE SPEAKER: Stephen Jones is a principal software engineer in the CUDA group at NVIDIA, working on making the CUDA language and programming model span the needs of parallel programming from high performance computing to artificial intelligence. Prior to NVIDIA he led the Simulation & Analytics group at SpaceX, where he worked on various projects including large-scale simulation of combustion processes in rocket engines. His background is in computational fluid mechanics and plasma physics, but he has worked in diverse industries including networking, CAD/CAM, and scientific computing.

SOUMITH CHINTALA

SOUMITH CHINTALA

AI Resarch Engineer, Facebook

PyTorch: A Framework for Fast, Dynamic Deep Learning and Scientific Computing

ABOUT THE SPEAKER: Soumith Chintala is an engineer at Facebook AI Research, where he works on deep learning and unsupervised learning. Soumith's work on adversarial networks and Torch has been featured in GTC keynotes by Jensen Huang.

MICHAL DROZDAL

MICHAL DROZDZAL

MONTREAL INSTITUTE FOR LEARNING ALGORITHMS, Post-Doctoral Researcher

Learning Normalized Inputs for Iterative Estimation in Medical Image Segmentation

ABOUT THE SPEAKER: Michal Drozdzal is a postdoctoral researcher at the Montreal Institute for Learning Algorithms. Michal’s research interests focus on designing machine learning approaches to tackle impactful problems present in medical imaging, including topics such as image segmentation, unsupervised learning, or learning from small amount of labeled data. Previously, he spent one year as postdoctoral researcher in Medtronic GI, working under the umbrella of Neurogut project, and one year at Polytechnique of Montreal, designing machine learning approaches for medical data analysis. Michal also collaborates with Imagia, a Montreal-based startup. He received his Ph.D. from the University of Barcelona, with a thesis on computer vision approaches to automation and discovery using wireless capsule endoscopy data.

CHEN FANG

CHEN FANG

ADOBE RESEARCH, Research Scientist

Learning-Free Universal Style Transformer

ABOUT THE SPEAKER: Chen Fang is a research scientist at Adobe Research. His research interests are Computer Vision and Machine Learning.

JULES URBACH

JULES URBACH

OTOY, CEO

Light Field Rendering and Streaming for VR and AR

ABOUT THE SPEAKER: Jules Urbach is a pioneer in computer graphics, streaming, and 3D rendering with over 25 years of industry experience. He made his first game, Hell Cab (Time Warner Interactive), at age 18, which was one of the first CD-ROM games ever created. Six years later, Jules founded Groove Alliance, which created the first 3D game ever available on Shockwave.com (Real Pool). Currently, Jules is busy working on his two latest ventures, OTOY and LightStage, which aim to revolutionize 3D content capture, creation, and delivery.

SANJA FIDLER

SANJA FIDLER

UNIVERSITY OF TORONTO, Assistant Professor

Teaching Machines to See, Communicate, and Act

ABOUT THE SPEAKER: Sanja Fidler is an Assistant Professor at the Department of Computer Science, University of Toronto.  Previously she was a Research Assistant Professor at TTI-Chicago, a philanthropically endowed academic institute located in the campus of the University of Chicago. She completed her PhD in computer science at  University of Ljubljana in 2010, and was a postdoctoral fellow at University of Toronto during 2011-2012. In 2010 she visited UC Berkeley. She has served as a Program Chair of the 3DV conference, and as an Area Chair of CVPR, ICCV, EMNLP, ICLR, and NIPS. She received the NVIDIA Pioneer of AI award. Her recent work on semi-automatic object labeling won the Best Paper Honorable mention at CVPR'17. Her main research interests are object detection, 3D scene understanding, and the intersection of language and vision.

ARPIT MEHTA

ARPIT MEHTA

BMW GROUP, Data Scientist

Beyond Autonomous Driving: Unleashing Value via Machine Learning Applications in Automotive Industry

ABOUT THE SPEAKER: Arpit Mehta is a data scientist and product owner for big data architecture at BMW Group. He is a machine learning, deep learning, and AI enthusiast, and works to bring them together to solve different business challenges. Arpit is also interested in evaluating newer technologies and defining new strategies for architecting data-driven production use cases.

DANNY ATSMON

DANNY ATSMON

COGNATA, CEO

Deep Learning Autonomous Driving Simulation

ABOUT THE SPEAKER: Danny Atsmon, an expert in advanced driver-assistance systems (ADAS) and deep learning, is the CEO at Cognata Ltd. He has been in the business of launching high-tech products for more than 20 years. Before joining Cognata, Danny served as HARMAN’s (now Samsung) director of ADAS and senior director of machine learning. He co-founded two startups, Picitup and iOnRoad, the latter of which uses a phone's native camera to detect vehicles in front of a car. Danny also holds several patents and has won many top industry awards, including the CES award, CTIA award, Microsoft Think Next, and Qualcomm QPrize. Danny has a Bachelor of Science in physics from Tel Aviv University, and is a graduate of the Israeli Defense Forces Haman Talpiot program, where he served in the elite Unit 8200.

XIAODONG HE

XIAODONG HE

MICROSOFT RESEARCH, Principal Researcher and Research Manager

Attention GAN for Fine-Grained Language-to-Image Generation

ABOUT THE SPEAKER: Xiaodong He is Principal Researcher and Research Manager of the Deep Learning Technology Center of Microsoft Research, Redmond, WA, USA. He is also an Affiliate Professor in the Department of Electrical Engineering at the University of Washington (Seattle). His research interests are mainly in artificial intelligence areas including deep learning, natural language, computer vision, speech, information retrieval, and knowledge representation. He has published more than 100 papers in ACL, EMNLP, NAACL, CVPR, SIGIR, WWW, CIKM, NIPS, ICLR, ICASSP, Proc. IEEE, IEEE TASLP, IEEE SPM, and other venues. He received Outstanding Paper Award at ACL 2015. He is also the inventor of the DSSM. He and colleagues has won multiple competitions including NIST MT 2008, IWSLT 2011, COCO image caption Challenge 2015, VQA Challenge 2017. He led the development of CaptionBot and Image Captioning Cloud Service (via CV API of Microsoft Cognitive Services) at Microsoft.

PIETER ABBEEL

PIETER ABBEEL

UC BERKELEY, Professor

Learning to Learn, Deep Learning for Robotics, Deep Reinforcement Learning, AI for Manufacturing and Logistics

ABOUT THE SPEAKER: Pieter Abbeel (Professor at UC Berkeley, Research Scientist at OpenAI, Co-Founder Gradescope) works in machine learning and robotics, in particular his research is on making robots learn from people (apprenticeship learning), how to make robots learn through their own trial and error (reinforcement learning), and how to speed up skill acquisition through learning-to-learn.  His robots have learned advanced helicopter aerobatics, knot-tying, basic assembly, and organizing laundry.  His group has pioneered deep reinforcement learning for robotics, including learning visuomotor skills and simulated locomotion. He has won various awards, including best paper awards at ICML, NIPS and ICRA, the Sloan Fellowship, the Air Force Office of Scientific Research Young Investigator Program (AFOSR-YIP) award, the Office of Naval Research Young Investigator Program (ONR-YIP) award, the DARPA Young Faculty Award (DARPA-YFA), the National Science Foundation Faculty Early Career Development Program Award

REV LEBAREDIAN

REV LEBAREDIAN

NVIDIA, VP, GameWorks and Lightspeed Studios

ABOUT THE SPEAKER: Rev Lebaredian started his career in Hollywood, specializing in rendering for Warner Bros. Digital and Disney’s Dream Quest Images. He developed the renderer used for the Academy Award nominated film Mighty Joe Young. He then formed Steamboat Software and developed the award-winning renderer Jig, used by visual effects studios such as Digital Domain, PDI/Dream Works, Sony ImageWorks, Walt Disney, and Rhythm and Hues for various films including X-Men 2, Stuart Little, The Core, Reign of Fire, Sum of All Fears, Treasure Planet, Gone in Sixty Seconds and How the Grinch Stole Christmas. In 2002, Rev transitioned from film visual effects to NVIDIA, where he helped in the creation of the Cg shading language. NVIDIA relocated Rev to Moscow to open a new site for NVIDIA and to architect a state-of-the-art games testing and data-mining lab, as well as NVIDIA’s groundbreaking client, GeForce Experience. Today, Rev is vice president of GameWorks and Lightspeed studios at NVIDIA, responsible for developing NVIDIA GameWorks technologies, first-party games, the Holodeck VR platform, and the Isaac Lab robot simulator. GameWorks includes various visual effects modules tailored for real-time high-fidelity applications, such as NVIDIA Destruction, NVIDIA Clothing, HairWorks, WaveWorks, Ansel, as well as the most popular real-time physics middleware for video games, PhysX.

VLADIMIR KOYLAZOV

VLADIMIR KOYLAZOV

CHAOS GROUP, CTO

Interactive and Production Rendering with V-Ray GPU

ABOUT THE SPEAKER: Vladimir Koylazov (Vlado) has more than 15 years of software development experience, the majority of which he spent developing and improving the render engine V-Ray. Passionate about 3D graphics and programming, Vlado is the driving force behind Chaos Group's software solutions. Vladimir is CTO of Chaos Software and one of the original creators of the V-Ray renderer.

WES ARMOUR

WES ARMOUR

UNIVERSITY OF OXFORD, DEPT OF ENGINEERING, Director

AstroAccelerate - GPU-Accelerated Signal Processing for Next Generation Radio Telescopes

ABOUT THE SPEAKER: Wes Armour is associate director at the Oxford e-Research Centre (OeRC). He leads the scientific computing group at OeRC, which has around 10 members. Wes’ grant portfolio spans a range of different funders, reflecting the interdisciplinary projects that the group is involved with. His research interests are strongly focused in scientific computing, specifically the use of HPC and many-core technologies to answer scientific problems or to impact people's daily lives. Wes’ work focuses are modeling and simulation, digital signal processing, HPC/many-core and real-time computing for big data/data science. Wes has a Master's of Physics in fundamental particle physics and cosmology and a Ph.D. in lattice gauge theory, the computational description of the strong nuclear force.

GAURAV BANSAL

GAURAV BANSAL

TOYOTA INFOTECHNOLOGY CENTER, USA, Principal Researcher

Connected Automated Driving: Overview, Design, and Technical Challenges

ABOUT THE SPEAKER: Gaurav Bansal is a principal researcher at the Toyota InfoTechnology Center in Mountain View, Calif., where he leads several research initiatives on the design of communication systems for automated driving. Gaurav is an expert in vehicular communications, pioneering contributions in dedicated short range communications (DSRC) congestion control and in innovative use-cases to leverage connectivity in cars. His research interests include cooperative perception and mapping for autonomous vehicles. Gaurav represents Toyota in the Automakers' Vehicle Safety Communication Consortium and in the SAE, ETSI standardization bodies. Gaurav's paper on DSRC congestion control received the Best Paper Award at the IEEE WiVEC Symposium. He also serves in the editorial board of IEEE Vehicular Technology Magazine and IEEE Connected Vehicles Initiative. Gaurav holds several patents, and has both a Bachelor of Technology and Ph.D. in electrical engineering from Indian Institute of Technology Kanpur and the University of British Columbia, respectively.

QING WANG

QING WANG

IBM RESEARCH CHINA, Research Staff Member

Using Multimodal Learning for TV Show Summarization

ABOUT THE SPEAKER: Qing Wang graduated from Electrical & Electronic Engineering School, Nanyang Technological University, Singapore in 2003 with Ph.D. After that, Qing joined IBM Research China as a research staff member and worked in leading research projects, such as wireless network cloud and Internet of Things. Since 2015, she has focused on computer vision with deep learning methods. Qing is a key contributor to the cloud-based deep learning platform called AI Vision. Her research interests include neural network auto design, multimodal learning, and medical image processing. She is an IEEE senior member, has published more than 30 papers, and has owned more than 20 patents.

FERNANDA FOERTTER

FERNANDA FOERTTER

OAK RIDGE NATIONAL LAB, HPC Data Scientist

Scaling Deep Learning for Scientific Workloads on Summit

ABOUT THE SPEAKER: Fernanda Foertter is a HPC Programmer at Oak Ridge National Lab.

OLGA PEARCE

OLGA PEARCE

LAWRENCE LIVERMORE NATIONAL LABORATORY, Computer Scientist

Acceleration of HPC Applications on Hybrid CPU-GPU Systems: When Can Multi-Process Service Help?

ABOUT THE SPEAKER: Olga Pearce is a computer scientist in the Center for Applied Scientific Computing (CASC) at Lawrence Livermore National Laboratory (LLNL). Her research interests include distributed data structures and parallel algorithms; parallel programing models; performance analysis, optimization, and modeling; and application load balancing. Olga applies her research by optimizing simulations on several supercomputers, including SEQUOIA. Olga joined LLNL in 2009 as a Lawrence Scholar and joined CASC in 2014. Olga received her Ph.D. in computer science in 2014 from Texas A&M University.

WILL RAMEY

WILL RAMEY

NVIDIA, Director, Developer Programs

Deep Learning Demystified

ABOUT THE SPEAKER: Will Ramey is director of developer programs at NVIDIA. Since joining the company in 2003 he has served in a number of marketing and management roles, including several years as the first product manager for CUDA and NVIDIA's developer tools. Currently Will leads teams responsible for promoting the NVIDIA SDK, developer programs, and the Deep Learning Institute. Prior to joining NVIDIA, he managed an independent game studio and developed advanced technology for the entertainment industry as a product manager and software engineer. He holds a BA in computer science from Willamette University and completed the Japan Studies Program at Tokyo International University. Outside of work Will enjoys the outdoors, learning Spanish, and open water swimming. Follow @wramey on Twitter to keep up with Will online.

PACKAGE COMPARISON

 
Conference
+ Training
Conference
EXHIBITS
Pre-conference
Training

Conference Sessions

 

 

Training / Hands-on Labs
(up to 3 per day)

 

 

 

Talks and Tutorials

 

 

Keynotes

 

 

Exhibits

 

Lunch

Evening Receptions

 

GTC Party1

 

 

Conference Materials2

 

Pre-GTC DLI Workshop
(Sunday, March 25)

 

 

 

1. Additional GTC Party passes available for purchase for a spouse/guest with a paid registration. Available as add-on for Exhibits Only or One-Day (other than Wednesday, 3/28) pass holders. GTC Party pass valid for access to party on Wednesday, 3/28 only; does not include any other conference privileges.

2. Conference materials include access to post event recordings and presentation files, and a GTC-branded bag and t-shirt.