Nvidia Accelerated Computing

Nine of the world’s fastest GPU supercomputers

Big and beefy heterogeneous HPC systems Read more


Leaps in Visual Computing

Watch the 2015 GPU Technology Conference Keynote
from Jen-Hsun Huang, Co-Founder and CEO, NVIDIA



Large-Scale Deep Learning
Featuring Jeff Dean, Senior Fellow, Google


What’s Next in Deep Learning
Featuring Andrew Ng, Chief Scientist, Baidu

Exploiting the OpenPOWER Platform for Big Data Analytics and Cognitive Computing

Rajesh Bordawekar (IBM T. J. Watson Research Center), Ruchir Puri (IBM Research)
In this session you will learn about how IBM is exploiting GPUs in its new IBM OpenPOWER platform for acceleration of Big Data Analytics and Cognitive Computing solutions.  It showcases recent successes in the use of GPUs to accelerate challenging molecular visualization and analysis tasks on hardware platforms ranging from commodity desktop computers to the latest Cray supercomputers.
 Watch the video

VMD: Visualization and Analysis of Biomolecular Complexes with GPU Computing

John Stone (University of Illinois at Urbana-Champaign)
This talk showcases recent successes in the use of GPUs to accelerate challenging molecular visualization and analysis tasks on hardware platforms ranging from commodity desktop computers to the latest Cray supercomputers.
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NVIDIA® NVLink™ is a high-bandwidth, energy-efficient interconnect that enables ultra-fast communication between the CPU and GPU, and between GPUs.


Download the NVIDIA® Tesla® K80 GPU performance benchmark infographic to see how you can boost the performance of your data center.

Automated Image Captioning with ConvNets and Recurrent Nets

Andrej Karpathy (Stanford University and Google Researcher)
A Meetup hosted by the Silicon Valley HPC &; GPU Supercomputing Meetup Group.
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GPUs to Mars: Full-Scale Simulation of SpaceX’s Mars Rocket Engine

Stephen Jones (SpaceX), Adam Lichtl (SpaceX)
SpaceX is designing a new, methane-fueled engine powerful enough to lift the equipment and personnel needed to colonize Mars. A vital aspect of this effort involves the creation of a multi-physics code to accurately model a running rocket engine. The scale and complexity of turbulent non-premixed combustion has so far made it impractical to simulate, even on today’s largest supercomputers. We present a novel approach using wavelets on GPUs, capable of capturing physics down to the finest turbulent scales.
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Statistics of the Universe: Exa-Calculations and Cosmology’s Data Deluge

Matthew Bellis (Siena College), Deborah Bard (SLAC National Accelerator Laboratory)
Learn how to use GPUs on the desktop to study the structure and evolution of the Universe: how galaxies are pulled together by gravity, and how space expands under the influence of Dark Energy. Metrics used to describe this structure are the two- and three-point correlation functions, which quantify the clustering of galaxies. Cosmological datasets can number in the millions (and soon billions) of galaxies, making these O(N^2) and O(N^3) metrics computationally challenging. This talk will detail how we have ported solutions to the GPU.
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Real-Time, Content-Driven Representations at Twitter

Clement Farabet (Twitter)
Twitter is a unique source of real-time information, offering amazing opportunities for automatic content understanding.  In this talk, I provide an overview of how automated, content-driven representationsenabled by modern deep-learning algorithmsenables us to build adaptive systems which capture the richness of this content. Specifically, the presentation focuses on deep representations for images and images+text.
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Map-D: Hyper-Interactive GPU-Powered Visualytics for Big Data

Todd Mostak (Map-D)
In this talk, we will argue that dense GPU servers, containing 4-16 GPUs each, can provide analytics query throughput exceeding what can be achieved on even large clusters, while avoiding the latencies and complications associated with running over a network. We will look at MapD, which can query and visualize multi-billion row datasets in milliseconds, as an example of such a system.
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Creating a “Snappy” Virtual Desktop User Experience

Aivars Apsite (Metro Health)
Metro Health will review their latest VDI implementation to address numerous performance issues, including graphics performance. They will address the need to have the VDI session be perceived as “snappy”. A definition of “snappy” will be provided, and metrics shown how snappy was improved with their new spec. Latency and IOPS will be discussed. Metro will show how their latest hardware specs have improved performance. Lastly, video processing and 3D graphics has been a performance challenge for virtual desktops. Metro will review how their use of the Teradici Apex CPU offload cards and NVIDIA K1 cards with the vSGA protocol improved their VDI video performance.
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Speech: The Next Generation

Bryan Catanzaro (Baidu)
Speech is the user interface of the future, but today’s implementations often fail when we need them the most, such as in noisy environments or when the microphone isn’t close at hand. At Baidu, an increasing fraction of our users employ speech interfaces to find what they are looking for. In this talk, I will show how next generation deep learning models can provide state-of-the-art speech recognition performance. We train these models using clusters of GPUs using CUDA, MPI and Infiniband.
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Exploring Design Considerations: CAD/CAM Experiences from the Experts Using Citrix and VMware

Fred Devoir (Textron Inc.), Randall Siggers (Textron Inc.)
Join an interactive discussion and Q&A session highlighting the design considerations for deployment of 3D remote graphics solutions with a focus on end-user experience as applied for use with CAD/CAM. Designing for user experience should include considerations for availability, performance, and personalization. Explore the different use cases for Citrix and VMware as applied for use with Autodesk AutoCAD, Dassault Catia, PTC ProEngineer, and Siemens NX. Included will be demonstrated tuning of Dassault Systèmes Catia V6 for Citrix XenDesktop, massive WriteCache design consideration for ANSYS, how to design for user concurrency without sacrificing performance or user experience, and VMware vGPU design considerations in regards to Autodesk on VMware Horizon View.
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