Gtc2013 recap


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Gtc2013 recap

  1. 1. Innovation ollaboration spiration GPUTechnology Conference
  2. 2. 2006 2007 2008 2009 2010 2011 2012 40 35 30 25 20 15 10 5 NVIDIA Acceleration 31 petaFLOPS Total Acceleration 37 petaFLOPS GPU‑Accelerated computinghas become an important catalyst in the advancement of science and technology—enabling tremendous breakthroughs by simply enabling us to do more, faster. The need to solve complex computational problems is becoming increasingly commonplace. And GPU-powered accelerated computing is meeting this need by delivering an order of magnitude more performance, more efficiently. Accelerator Performance in Supercomputing Performance delivered by GPUs in supercomputers has increased from 0 to 19% in five years and is growing exponentially. Source:
  3. 3. Developing with GPUs is now pervasive in computing: 430,000,000+CUDA GPUs have been shipped 35,000+papers have been published on CUDA 8,000+institutions have registered CUDA developers 580+universities are teaching GPU programming 200+major applications are now GPU accelerated 50+of the world’s fastest supercomputers are powered by CUDA GPUs The benefits of GPU‑accelerated computing are more widely recognized every day. This is leading to more industry leaders and members of the research community to adopt both NVIDIA GPUs and CUDA ® , the world’s most pervasive parallel‑computing platform and programming model. That’s more than two shipped every second!
  4. 4. Driven by the broad use of NVIDIA visual computing technology, the GPU Technology Conference (GTC) has become the world’s most important event for GPU developers. GTCis where art meets sciencemeets engineering meets business.
  5. 5. Air Force Research Lab Barcelona Supercomputing Center BGI Carnegie Mellon Chinese Academy of Sciences CERN ETRI Korea Expressions College for Digital Arts Fermi National Accelerator Lab Georgia Tech Harvard IIT Italy JPL Johns Hopkins Julich Supercomputing Center KAUST Los Alamos National Lab MIT Lincoln Lab NASA NATO Naval Air Warfare Center NOAA Oak Ridge National Lab Russian Academy of Sciences Sandia National Lab Stanford Swiss Supercomputing Center Tokyo Tech Audi Amazon Apple Bank of America BMW Boeing Carl Zeiss Chevron Chrysler Deutsche Telecom ESPN E*Trade Exxon Mobile Fiat Ford Google Goldman Sachs Gulfstream Aerospace Harley Davidson Honda Research iRobot LEGO NASDAQ Netflix Nike Pixar Space-X Tesla Motors Walt Disney Academic and Research Industry Every year, GTC provides an important venue for exploring the game- changing impact GPUs deliver to science, technology, and industry. And the 2013 event was one of the most impressive ever. The four‑day conference featured talks by industry and NVIDIA experts on GPU-accelerated computing—from problem solving in everything from medicine to product design and big data, to hands-on sessions on how to take advantage of this disruptive technology. More than 3,000Attendees from over 50countries 425Conference Sessions 150Research Posters Here’s a sampling of organizations that attended GTC 2013:
  6. 6. GPUs are already finding their way into systems and applications that were undreamed of a decade ago. Soon, mobile, desktop, and supercomputer technologies will intersect in powerful and surprising ways. Accelerating The Future
  7. 7. GTC 2013 also featured the unveiling of several technologies that will impact the future of computing. This included the introduction of the NVIDIA GRID ™  VCA, the industry’s first Visual Computing Appliance. The GRID VCA enables businesses to deliver ultra- fast GPU performance to any Windows, Linux, or Mac client device on their network while providing the same rich graphic user experience as a dedicated desktop PC or workstation. GRID VCA provides a workstation-quality experience on any PC, Mac, or Linux device and runs applications for power users such as those from Adobe, Autodesk, and Dassault Systems. It is a turnkey appliance that is easy to install and manage.
  8. 8. At GTC 2013, NVIDIA unveiled its GPU architecture roadmap, demonstrating that NVIDIA continues to focus on dramatically improving performance while also improving energy efficiency. Today, its Kepler™ architecture is at the heart of the fastest, most energy-efficient accelerators, including those that power the world’s fastest supercomputer for open science. The next-generation Maxwell architecture will deliver unified virtual memory, increasing the performance and shortening development time for application developers. The Volta architecture will follow, which is designed to solve one of the biggest challenges of computing today—memory bandwidth. 2008 2010 2012 2014 Tesla CUDA Fermi Full Double Precision Kepler Dynamic Parallelism Maxwell Unified Virtual Memory Volta Stacked DRAM 32 16 8 4 2 1 0.5 DoublePrecisionGigaFLOPSper Watt The next-generation Maxwell architecture will deliver unified virtual memory, followed by the Volta architecture that’s designed to achieve 1 TB/sec of memory bandwidth, equivalent to transferring the entire contents of a Blue-ray DVD in 1/50th of a second.
  9. 9. 2011 2012 2013 2014 2015 100 10 1 RelativePerformance Tegra 2 First Dual A9 Tegra 3 First Quad A9 First Power‑Saver Core Tegra 4 First LTE SDR Modem Computational Camera Logan Kepler-Based GPU CUDA OpenGL 4.3 Parker Denver-Based CPU Maxwell-Based GPU FinFET The NVIDIA Tegra ® Mobile processor roadmap was also unveiled at the conference. It demonstrated that NVIDIA’s investment in computing is everywhere—not just in PCs and datacenters, but also in cars, phones, tablets, gaming portables, and anything with a display. For example, Tegra 4 leverages the CPU, GPU, and ISP to deliver advanced computational photography features like real-time HDR and intelligent object tracking. Tegra 4 will be followed by Project Logan, which pairs ARM® -based mobile processor cores with our Kepler GPUs. This will be followed by Project Parker, which will join the new 64‑bit, ARM-compatible CPU cores with our next-generation Maxwell GPU architecture. Tegra 4 will be followed by Logan, bringing technologies currently found in high‑performance PCs and workstations to mobile devices. With Parker, a server‑class CPU will be combined with our Maxwell GPU’s unified virtual memory and advanced performance per watt.
  10. 10. To address the industry’s requirement for developing applications for low-power architectures, NVIDIA also introduced the Kaylaplatform —the ARM development platform for mobile computing and HPC applications. It’s designed to deliver the highest performance and efficiency for the widest range of next- generation ARM-based OpenGL and CUDA applications by combining a Tegra quad-core ARM processor with a Kepler-based GPU. This gives developers a great way to take advantage of the next-gen Tegra SoCs based on the Logan architecture. Real-time ray tracing, FFT‑based ocean simulation, and smoke-particle simulation on the Kayla platform.
  11. 11. Accelerating Industry >> safer and smarter automobiles >> medical applications, including 4D heart ultrasound that can potentially save lives >> cinema and special effects >> geospatial intelligence made possible by video and image processing >> digital product design across various industries >> big data analytics applied to every day uses Taking center stage at the conference were breakthroughs in various fields—from science to a wide range of industries—spurred on by accelerated computing. GTC 2013 showcased a number of industry-changing discoveries made possible by GPUs. These included:
  12. 12. Imaging capabilities in broadcast media have progressed by leaps and bounds over the last few decades, especially in sports broadcasting. This provides today’s sports fans with a far more intimate and entertaining experience in the games they love. The ESPN Emerging Technology Group is behind many of these technology breakthroughs. Based on an idea from a prior GTC, ESPN developed a software architecture for sports broadcasts using NVIDIA GPUs. Today ESPN is using GPUs to convert 4K video input for spectacular “lossless” zoom to 720p for sports broadcasts. Virtual cameras, real-time overlay effects, and other features deliver a closer, enhanced experience of sports broadcasts to viewers. Harley-Davidson has been designing and manufacturing motorcycles for more than a century. Today, they still produce vehicles that are coveted by one of the most loyal customer bases in the world. In recent years, the design process has evolved to include digital visualization tools during the conceptual phase, between styling and engineering. GPU- accelerated industrial design integrates art with modeling and simulation, ultimately reducing time for product development, improving styling intent, allowing greater conceptual exploration, and delivering higher-quality designs earlier. Bringing Fans Closer to the Game ESPN Melding Art and Simulation in Industrial Design Harley-Davidson Motor Company
  13. 13. GTC 2013 featured presenters from Audi, BMW, Chrysler, Fiat, Honda, and Peugeot Citroen sharing breakthroughs in how GPUs are increasingly playing a central role in auto safety and infotainment systems, as well as breakthroughs in design. Researchers from Audi revealed how GPUs are used as part of an initiative to make driving safer in urban areas. Highly intelligent, power‑efficient systems in cars will soon suggest when to leave for your daily commute, whether or not to stop for coffee, even where to find best parking choices, all based on real‑time information. It’s all about communicating with the driver in an intuitive, non‑distracting way. Navigating Chaotic Roadways More Safely Audi Better Safety and Infotainment in Cars GPUs are increasingly playing a central role in auto safety and infotainment systems. Companies including Audi and Lamborghini have already adopted NVIDIA technology, and it will soon power models from BMW, Tesla Motors, Mini, and Rolls Royce, among others. For instance, researchers from Audi revealed how they are processing big data in real-time to make driving safer in urban areas, eliminate traffic bottlenecks, and make parking more efficient. Honda Research is also working on future technologies, such as merging of digital instrument clusters and head-up displays. And researchers at Carnegie Mellon are using GPUs to enable gesture recognition and natural language processing, enabling a new generation of human machine interfaces to be developed for safer in‑vehicle use. With increasing demand for advanced, power-efficient computing, NVIDIA unveiled the Jetson automotive development platform at GTC. With this car stereo sized system, developers can easily create and test automotive, image processing, and computer- vision applications.
  14. 14. Shazam is a commercial mobile phone-based music identification service that connects more than 300 million people in more than 200 countries and 33 languages. It uses GPUs to instantly search and identify songs from its 27 million track database more than 10 million times a day. This is accomplished by assigning an acoustic fingerprint to each song sample, matching that sample to their track library, and returning the answer in just a few seconds. Today, every search is done using GPUs. Because of the performance and power efficiency of the GPU, Shazam is able to scale the operations at less than half the cost. Identifying Audio Patterns Shazam Big Data Trend This year’s conference highlighted a growing trend of top enterprise and mobile application companies like IBM and Groupon using GPUs to accelerate consumer and commercial big data applications. Industry leaders such as Shazam, as well as pioneering startup Cortexica, also use GPUs to accelerate large-scale audio search, real- time Twitter analysis, and image matching. In each use case, GPUs dramatically accelerate the processing of massive datasets with complex algorithms, and make it possible for these big data companies to scale their infrastructure cost effectively to meet growing demand.
  15. 15. Accelerating Science >> intelligent object recognition by robots and cars >> image processing for geospatial intelligence >> 3D visualization, better weather prediction for disaster prevention >> affordable whole genome sequencing to predict genetic defects and diseases GTC has also been the venue for the latest breakthroughs in science and research on a variety of topics. These included:
  16. 16. Stretch a strand of human DNA out to its full length and it’s two meters long. Yet all that material—and the information it carries—gets balled up inside the nucleus of a single cell. By unraveling the human genome, we can unlock the mysteries around genetic causes of disease and the environmental factors that impact genetic behavior. Using GPUs, Harvard Fellow Erez Lieberman‑Aiden discovered that DNA comes together in fractal globules (the same shape as uncooked ramen noodles) and its folds determine whether healthy or malignant cells will be produced. The technique relies on looking at the billions of snapshots generated by modern DNA sequencing techniques and comparing their 3D relationships. GPUs are essential in analyzing the enormous amount of data at the heart of the process that enables researchers to map out a person’s genome and predict diseases. Better Human Genome Mapping and Disease Prediction Baylor College of Medicine Rice University Faster, Affordable Gene Sequencing GPU-accelerated gene sequencing is driving down the cost of genomic research significantly. The cost to sequence an entire human genome can be reduced to $1000 very soon. “By democratizing genome sequencing, we expect to see an unprecedented wave of innovation in life sciences.” — Alan Williams, Life Technologies
  17. 17. Imagine the impact on public safety if we could pinpoint a significant natural disaster such as the landfall of Hurricane Sandy five days in advance. Our ability to do that may be closer than you realize. The National Oceanic and Atmospheric Administration (NOAA) presented the latest research in high-resolution weather models. Such computationally intense models were able to pinpoint the landfall of major storms and hurricanes such as Sandy. GPU computing will be essential to the daily use of highly accurate models for operational weather modeling, delivering better power and cost efficiency in data centers. Accurate Weather Modeling and Prediction NOAA Earth System Research Laboratory
  18. 18. The floors of the Adriatic and Mediterranean seas are littered with tens of thousands of mines, bombs, and other munitions that were lost or abandoned after World War I and II. To locate and identify the dangerous materials, NATO is using autonomous underwater vehicles equipped with synthetic aperture sonar (SAS) running on GPUs. The SAS application runs up to 100X faster with GPUs, enabling real-time object recognition and intelligent decision- making capabilities within the vehicle’s six-hour operational window. With GPU acceleration, mine hunting is faster, more affordable, more reliable, and safer. Real-Time Mine Hunting with Unmanned Submarines NATO STO Centre for Maritime Research and Exploration Istituto Italiano di Tecnologia, Italy Researchers have long believed that human cognition is developed through interacting with the environment and other humans using limbs and senses. And that human-like manipulation plays a vital role in the development of the cognition. At Plymouth University, researchers are contributing to the emergence of humanoid robots by modeling biological neural networks to better understand both human cognition and artificial intelligence. These networks consist of thousands of neurons connected to each other through millions of synapses. The systems integrate visual processing, linguistics, and other inputs such as touch, temperature, and position. This is made possible with GPUs that perform the millions of calculations to activate the neural network every 50-100 milliseconds, allowing researchers to teach the robot to think like a human. Robot Cognition: Thinking Like Humans Plymouth University
  19. 19. GPU Supercomputing On the Rise At GTC, the Swiss National Supercomputing Center announced it will deploy NVIDIA GPUs to build Europe’s fastest GPU supercomputer. Piz Daint will be used for scientific discovery in weather modeling, astrophysics, material science, and life science—the latest evidence that GPU computing has passed the tipping point. GPU accelerators have evolved into general-purpose processors ideally suited to tackle massively parallel computing problems. Today, more than 50 systems on the Top500 list of supercomputers are powered by GPUs. At GTC, representatives from Oak Ridge National Laboratory presented early science on the Titan supercomputer—the world’s fastest for open science—as well as how researchers and scientists can gain access to this powerful computing resource. Titan delivers peak performance of 27 petaflops, with 18,688 GPUs providing 90% of the computing power, and is open to academia, government labs, and industry from across the globe. Powering the Biggest Breakthroughs Oak Ridge National Laboratory
  20. 20. GTC is where researchers, developers, and technologists from around the globe meet to learn how others are solving the toughest computational problems. “It is the best conference for meeting peoples—it even beats Supercomputing.” — Guido Juckeland, Sr. Systems Engineer, TU Dresden “Unbelievable, to see in the same place financial engineers, physicians, astrophysicists, game creators… It is the only event in the world where you can see all those talented people!” — Jonathan Lellouche, Quantitative Analyst, MUREX “GTC is action-packed and stimulating like no other conference. NVIDIA has placed scientific content top and center of GTC, while at the same time organizing an exciting program with educational sessions, stunning demos, and great networking opportunities. There will be so many people there that I want to meet again or for the first time. GTC is simply too good to pass [up].” — Lorena Barba, Assistant Professor, Boston University “I was really impressed with the breadth of the subjects and the focus on performance. Really impressive.” — Mikael Sorboen, Head of Risk Systems, BNP Paribas “Every year I’ve made a lot of important contacts for new directions for my research.” — Peter Lu, Post-Doctoral Research Fellow, Harvard University “Though it was my first GTC, I was blown away. I felt like an ant in New York City, but in a good way. Interacting with strangers across the spectrum and knowing that there was so much to learn from them was mind‑blowing, but an amazing feeling.” — David Norman, Engineer/Tool Developer, The Boeing Company
  21. 21. Now that you’ve seen a sampling of how GPU- accelerated computation is impacting science and industry, exploreany of the 425 GTC sessionsfor yourself: More breakthrough researchis happening across the globe that will contribute to advances in science and technology. Check out GTC posters for the next game changer: We invite you to experience GTC 2013 virtually. Learn more about how GPUs can accelerate your work, and contact us if you would like additional information: ©2013 NVIDIA, the NVIDIA logo, CUDA, NVIDIA GRID, Kepler, Tegra, and Tesla are trademarks and/or registered trademarks of NVIDIA Corporation in the United States and other countries. Other company and product names may be trademarks of the respective companies with which they are associated. All rights reserved. MAY2013