This document discusses how mathematics and parallel computing powered by NVIDIA GPUs are driving the 21st century industrial revolution. It provides examples of how GPU computing is used across industries like drug design, automotive design, medical imaging, astrophysics, and more. It also discusses how GPUs are used in supercomputers and how this green technology is powering scientific discovery at lower costs using industry standard tools. Overall, the document promotes NVIDIA's GPU computing solutions and their wide applications.
In a series of announcements that left more than 1,200 gamers gathered in Cologne alternately breathless, giddy with laughter, and shouting their enthusiasm, Jensen Huang introduced the GeForce RTX series of gaming processors, representing the biggest leap in performance in NVIDIA’s history.
For the full video of this presentation, please visit:
https://www.edge-ai-vision.com/2021/02/tackling-extreme-visual-conditions-for-autonomous-uavs-in-the-wild-a-presentation-from-skydio/
Hayk Martiros, Head of Autonomy at Skydio, presents the “Tackling Extreme Visual Conditions for Autonomous UAVs In the Wild” tutorial at the September 2020 Embedded Vision Summit.
Skydio ships autonomous robots that are flown at scale in complex, unknown environments every day to capture incredible video, automate dangerous inspections and save lives of first responders. They must make decisions at high speed using just their onboard cameras and algorithms running on low-cost hardware. The company has invested five years of R&D into handling extreme visual scenarios not typically considered by academia nor encountered by cars, ground-based robots or AR applications.
Drones are commonly used in scenes with few or no semantic priors on the environment and must deftly navigate in the presence of thin objects, extreme lighting, camera artifacts, motion blur, textureless surfaces, vibrations, dirt, smudges and fog. Because photometric signals are not consistent, these challenges are daunting for both classical vision approaches and unsupervised learning. And there is no ground truth for direct supervision. Martiros takes a detailed look at these issues and how his company tackled them to push autonomous flight into production.
In a series of announcements that left more than 1,200 gamers gathered in Cologne alternately breathless, giddy with laughter, and shouting their enthusiasm, Jensen Huang introduced the GeForce RTX series of gaming processors, representing the biggest leap in performance in NVIDIA’s history.
For the full video of this presentation, please visit:
https://www.edge-ai-vision.com/2021/02/tackling-extreme-visual-conditions-for-autonomous-uavs-in-the-wild-a-presentation-from-skydio/
Hayk Martiros, Head of Autonomy at Skydio, presents the “Tackling Extreme Visual Conditions for Autonomous UAVs In the Wild” tutorial at the September 2020 Embedded Vision Summit.
Skydio ships autonomous robots that are flown at scale in complex, unknown environments every day to capture incredible video, automate dangerous inspections and save lives of first responders. They must make decisions at high speed using just their onboard cameras and algorithms running on low-cost hardware. The company has invested five years of R&D into handling extreme visual scenarios not typically considered by academia nor encountered by cars, ground-based robots or AR applications.
Drones are commonly used in scenes with few or no semantic priors on the environment and must deftly navigate in the presence of thin objects, extreme lighting, camera artifacts, motion blur, textureless surfaces, vibrations, dirt, smudges and fog. Because photometric signals are not consistent, these challenges are daunting for both classical vision approaches and unsupervised learning. And there is no ground truth for direct supervision. Martiros takes a detailed look at these issues and how his company tackled them to push autonomous flight into production.
Implementing AI: High Performance Architectures: A Universal Accelerated Comp...KTN
The Implementing AI: High Performance Architectures webinar, hosted by KTN and eFutures, was the fourth event in the Implementing AI webinar series.
The focus of the webinar was the impact of processing AI data on data centres - particularly from the technology perspective. Timothy Lanfear, Director of Solution Architecture and Engineering EMEA, NVIDIA, presented on a Universal Accelerated Computing Platform.
Opening Keynote at GTC 2015: Leaps in Visual ComputingNVIDIA
NVIDIA CEO and co-founder Jen-Hsun Huang took the stage for the GPU Technology Conference in the San Jose Convention Center to present some major announcements on March 17, 2015. You'll find out how NVIDIA is innovating in the field of deep learning, what NVIDIA DRIVE PX can do for automakers, and where Pascal, the next-generation GPU architecture, fits in the new performance roadmap.
NVIDIA CEO Jen-Hsun Huang introduces NVLink and shares a roadmap of the GPU. Primary topics also include an introduction of the GeForce GTX Titan Z, CUDA for machine learning, and Iray VCA.
Enabling Artificial Intelligence - Alison B. LowndesWithTheBest
An overview and update of our hardware and software offering and support provided to the Machine & Deep Learning Community around the world.
Alison B. Lowndes, AI DevRel, EMEA
At the 2018 GPU Technology Conference in Silicon Valley, NVIDIA CEO Jensen Huang announced the new "double-sized" 32GB Volta GPU; unveiled the NVIDIA DGX-2, the power of 300 servers in a box; showed an expanded inference platform with TensorRT 4 and Kubernetes on NVIDIA GPU; and revealed the NVIDIA GPU Cloud registry with 30 GPU-optimized containers and made it available from more cloud service providers. GTC attendees also got a sneak peek of the latest NVIDIA DRIVE software stack and the next DRIVE AI car computer, "Orin," along with developments in the NVIDIA Isaac platform for robotics and Project Clara, NVIDIA's medical imaging supercomputer.
NVIDIA CEO Jensen Huang's keynote address at the GPU Technology Conference 2019 (#GTC19) in Silicon Valley, where he introduced breakthroughs in pro graphics with NVIDIA Omniverse; in data science with NVIDIA-powered Data Science Workstations; in inference and enterprise computing with NVIDIA T4 GPU-powered servers; in autonomous machines with NVIDIA Jetson Nano and the NVIDIA Isaac SDK; in autonomous vehicles with NVIDIA Safety Force Field and DRIVE Constellation; and much more.
Tesla 2009-2013 and beyond. Check out the amazing progress we've made in the past 4 years This is a presentation made by my colleague Sumit Gupta at the NVIDIA investor Day 11 April 2013.
The presentation will introduce Nvidia and the concept of GPU computing in the context of Financial Services industry. Customer successes are referenced where dramatic speed-ups in performance have been achieved.
Implementing AI: High Performance Architectures: A Universal Accelerated Comp...KTN
The Implementing AI: High Performance Architectures webinar, hosted by KTN and eFutures, was the fourth event in the Implementing AI webinar series.
The focus of the webinar was the impact of processing AI data on data centres - particularly from the technology perspective. Timothy Lanfear, Director of Solution Architecture and Engineering EMEA, NVIDIA, presented on a Universal Accelerated Computing Platform.
Opening Keynote at GTC 2015: Leaps in Visual ComputingNVIDIA
NVIDIA CEO and co-founder Jen-Hsun Huang took the stage for the GPU Technology Conference in the San Jose Convention Center to present some major announcements on March 17, 2015. You'll find out how NVIDIA is innovating in the field of deep learning, what NVIDIA DRIVE PX can do for automakers, and where Pascal, the next-generation GPU architecture, fits in the new performance roadmap.
NVIDIA CEO Jen-Hsun Huang introduces NVLink and shares a roadmap of the GPU. Primary topics also include an introduction of the GeForce GTX Titan Z, CUDA for machine learning, and Iray VCA.
Enabling Artificial Intelligence - Alison B. LowndesWithTheBest
An overview and update of our hardware and software offering and support provided to the Machine & Deep Learning Community around the world.
Alison B. Lowndes, AI DevRel, EMEA
At the 2018 GPU Technology Conference in Silicon Valley, NVIDIA CEO Jensen Huang announced the new "double-sized" 32GB Volta GPU; unveiled the NVIDIA DGX-2, the power of 300 servers in a box; showed an expanded inference platform with TensorRT 4 and Kubernetes on NVIDIA GPU; and revealed the NVIDIA GPU Cloud registry with 30 GPU-optimized containers and made it available from more cloud service providers. GTC attendees also got a sneak peek of the latest NVIDIA DRIVE software stack and the next DRIVE AI car computer, "Orin," along with developments in the NVIDIA Isaac platform for robotics and Project Clara, NVIDIA's medical imaging supercomputer.
NVIDIA CEO Jensen Huang's keynote address at the GPU Technology Conference 2019 (#GTC19) in Silicon Valley, where he introduced breakthroughs in pro graphics with NVIDIA Omniverse; in data science with NVIDIA-powered Data Science Workstations; in inference and enterprise computing with NVIDIA T4 GPU-powered servers; in autonomous machines with NVIDIA Jetson Nano and the NVIDIA Isaac SDK; in autonomous vehicles with NVIDIA Safety Force Field and DRIVE Constellation; and much more.
Tesla 2009-2013 and beyond. Check out the amazing progress we've made in the past 4 years This is a presentation made by my colleague Sumit Gupta at the NVIDIA investor Day 11 April 2013.
The presentation will introduce Nvidia and the concept of GPU computing in the context of Financial Services industry. Customer successes are referenced where dramatic speed-ups in performance have been achieved.
A talk on reducing costs & increasing efficiencies by designing, testing & engineering in simulation first, plus examples of robotics & environmental capability.
Semiconductors are the driving force behind the AI evolution and enable its adoption across various application areas ranging from connected and automated driving to smart healthcare and wearables. Given that, electronics research, design and manufacturing communities around the world are increasingly investing in specialized AI chips providing less latency, greater processing power, higher bandwidth and faster performance. AI also attracts new technology players to invest in making their own specialized AI chips, changing the electronics manufacturing landscape and moving the AI technology towards machine learning, deep learning and neural networks.
VMworld 2013
Geoff Murase, VMware
Will Wade, NVIDIA
Learn more about VMworld and register at http://www.vmworld.com/index.jspa?src=socmed-vmworld-slideshare
Palestra apresentada por Pedro Mário Cruz e Silva, Solution Architect da NVIDIA, como parte da programação da VIII Semana de Inverno de Geofísica, em 19/07/2017.
As artificial intelligence sweeps across the technology landscape, NVIDIA unveiled today at its annual GPU Technology Conference a series of new products and technologies focused on deep learning, virtual reality and self-driving cars.
TiECon Florida keynote - New opportunities for entrepreneurs using GPU & CUDAShanker Trivedi
This is a presentation that I gave at TiEcon Florida on 20 Sept 2013. I spoke about the new opportunities that are emerging for entrepreneurs caused by the disruptive innovation potential of GPU, CUDA and parallel computing technologies.
Silicom Ventures Talk Aug 2013 - GPUs and Parallel Programming create new opp...Shanker Trivedi
GPU are delivering exponential improvements in computing performance and scalability. And new parallel programming architectures such as CUDA are allowing smart technologists to harness the power of GPUs to address hitherto insoluble problems. This talk will illustrate the emerging opportunities and solutions that GPUs and parallel programming can offer in medical instruments and imaging, defense and surveillance, autonomous vehicles, the internet of things and sensory computing, manufacturing design and simulation, and seismic geology. The talk will be relevant to entrepreneurs who are thinking about the "next big thing" and to investors who may be thinking of the future mega trends.
Presentation by Jonathan Cohen & Mark Berger at Bioinformatics conference July 2013. It covers
- GPU Programming in 10 slides
- GPUs in Bioinformatics
- Porting SeqAn to CUDA
- Resources for developers and bioinformatics professionals
Simple guide to understanding customers needs and positioning the best Nvidia solution, This is an easy-to-use Sales Guide that we provide to our partners.
We have made significant progress over the past couple of years working with scientists around the world helping them to accelerate scientific discovery - using Nvidia Tesla GPU and CUDA computing
5. Super Computing Across Industries
Drug Design Seismic Imaging Automotive Design Medical Imaging
Molecular Dynamics Reverse Time Migration Computational Fluid Dynamics Computed Tomography
Astrophysics Options Pricing Product Development Weather Forecasting
n-body Monte Carlo Finite Difference Time Domain Atmospheric Physics
NVIDIA Confidential
5
18. Additional Materials
! “Illumination Effect in Reverse Time Migration”, Bruno Kaelin et
al
! http://www.fusiongeo.com/publications/k3d/3DGeo-
IlluminationEffects_EAGE2007.pdf
! “Implementing 3D Finite Difference Codes on the GPU” by P.
Micikevicius
! Slides: http://www.nvidia.com/content/GTC/documents/1006_GTC09.pdf
! Video :
http://developer.download.nvidia.com/compute/cuda/docs/
GTC09Materials.htm (talk 1006P
19. CUDA Resources
! Introduction (basics, assume no GPU knowledge):
! Video: http://developer.download.nvidia.com/CUDA/training/cudaintrowebinar.mp4
! Slides: http://www.nvidia.com/content/PDF/sc_2010/CUDA_Tutorial/SC10_CUDA_C_Basics.pdf
! Fundamental optimization:
! The two presentations are largely the same, the second one has some updates but no audio/video
! Slides/video: http://www.nvidia.com/object/gtc2010-presentation-archive.html#session2011
! http://www.nvidia.com/content/PDF/sc_2010/CUDA_Tutorial/SC10_Fundamental_Optimizations.pdf
! Advanced optimization:
! The two presentations are largely the same, the second one has some updates but no audio/video
! Slides/video: http://www.nvidia.com/object/gtc2010-presentation-archive.html#session2012
! http://www.nvidia.com/content/PDF/sc_2010/CUDA_Tutorial/SC10_Analysis_Driven_Optimization.pdf
! Miscellaneous:
! all NVIDIA webinars: http://developer.nvidia.com/object/gpu_computing_online.html#Previously
! all NVIDIA tutorials from Supercomputing 2010: http://www.nvidia.com/object/sc10_cuda_tutorial.html
20. ICME Stanford
May 7, 2011
Shanker Trivedi
VP, Business Development