NVIDIA GPU TECHNOLOGY THEATER AT SC13
* Information subject to change. All times listed in Mountain Time Zone (GMT-7)
Monday, November 18 – Thursday, November 21 during exhibition hours | NVIDIA Booth #613
The NVIDIA GPU Technology Theater is hosting an amazing lineup of industry luminaries, scientists, and developers at SC13, covering
a wide range of topics on HPC and accelerated computing.
Come back often for updates!
Monday, November 18 | Booth #613

New Features in NVIDIA®
CUDA® 6 Make GPU
Acceleration Easier
8:00 PM – 8:30 PM

The performance and efficiency of CUDA, combined with a thriving ecosystemof programming languages, libraries, tools, training, and services, have helped
make GPU computing a leading HPC technology. Learn how powerful newfeatures in CUDA 6 make GPU computing easier than ever, helping you
accelerate more of your application with much less code.

Mark Harris
Chief Technologist GPU
Computing
NVIDIA

Tuesday, November 19 | Booth #613

Towards Performance-Portable
Applications Through Kokkos: A
Case Study with LAMMPS
10:30 AM – 11:00 AM

In this talk we demonstrate how LAMMPS uses the many-core device
performance portability library Kokkos to implement a single code base forCPUs, NVIDIA GPUs and Intel Xeon Phi co-processors. This portable code basehas equal or better performance compared to LAMMPS' current generation of
hardware specific add-on packages.

Christian Trott Postdoctoral
Appointee
Sandia National Laboratories
Massively Parallel Computing
and the Search for New Physics
at the LHC
11:00 AM – 11:30 AM
Valerie Halyo
Assistant Professor of Physics
Princeton University

The quest for rare new physics phenomena at the LHC leads us to evaluate aGraphics Processing Unit (GPU) enhancement of the existing High-Level Trigger(HLT), made possible by the current flexibility of the trigger system, which not
only provides faster and more efficient event selection, but also includes thepossibility of new complex triggers that were not previously feasible. A new
tracking algorithm is evaluated on a NVIDIA Tesla K20c GPU, allowing for the
first time the reconstruction of long-lived particles or displaced black holes inthe silicon tracker system at real time in the trigger.

* Information subject to change. All times listed in Mountain Time Zone (GMT-7)

Being Very Green with
Tsubame 2.5 Towards 3.0 and
Beyond to Exascale
11:30 AM – 12 Noon

TSUBAME 2.5 succeeded TSUBAME 2.0 by upgrading all 4224 Tesla M2050
GPUs to Kepler K20x GPUs, achieving 5.76 / 17.1 Petaflops peak in double /single point precision respectively, latter the fastest in Japan. By overcoming
several technical challenges, TSUBAME 2.5 exhibits x2-3 speedup and multipetaflops performance for many applications, leading to TSUBAME 3.0 in 201516.

Satoshi Matsuoka
Professor
Global Scientific Information
and Computing Center(GSIC), Tokyo Institute ofTechnology

Efficiency and Programmability:
Enablers for Exascale
12 Noon – 12:30 PM
Bill Dally
Chief Scientist & SVP Research
NVIDIA

Accelerated Computing with
OpenACC
12:30 PM – 1:00 PM

HPC and data analytics share challenges of power, programmability, andscalability to realize their potential. The end of Dennard scaling has made allcomputing power limited, so that performance is determined by energy
efficiency. With improvements in process technology offering little increase inefficiency, innovations in architecture and circuits are required to maintain the
expected performance scaling. The large scale parallelism and deep storage
hierarchy of future machines poses programming challenges. This talk will
discuss these challenges in more detail and introduce some of the technologies
being developed to address them.
The OpenACC API provides a high-level, performance portable programming
mechanism for parallel programming accelerated nodes. Learn about thelatest additions to the OpenACC specification, and see the PGI Accelerator
compilers in action targeting the fastest NVIDIA GPUs.

Michael Wolfe
Compiler Engineer
The Portland Group, NVIDIA
New Features in CUDA 6 Make
GPU Acceleration Easier
1:00 PM – 1:30 PM

The performance and efficiency of CUDA, combined with a thriving ecosystemof programming languages, libraries, tools, training, and services, have helped
make GPU computing a leading HPC technology. Learn how powerful newfeatures in CUDA 6 make GPU computing easier than ever, helping you
accelerate more of your application with much less code.

Mark Harris
Chief Technologist, GPU
Computing
NVIDIA* Information subject to change. All times listed in Mountain Time Zone (GMT-7)

Titan: Accelerating
Computational Science andEngineering with Leadership
Computing

1:30 PM – 2:00 PM

Modeling and simulation with petascale computing has supercharged theprocess of innovation, dramatically accelerating time-to-discovery. This
presentation will focus on early science from the Titan supercomputer at the
Oak Ridge Leadership Computing Facility, with results from scientific codes
discuss, e.g., LAMMPS and WL-LSMS. I will also summarize the lessons wehave learned in preparing applications to move from conventional CPU
architectures to a hybrid, accelerated architecture, and the implications for the
research community as we prepare for exascale computational science.

Jack Wells
Director of Science
National Center for
Computational Science Oak
Ridge National Laboratory
A Productive Framework for
Generating High-Performance,
Portable, Scalable Applicationsfor Heterogeneous Computing
2:00 PM – 2:30 PM

I will present two synergistic systems that enable productive development of
scalable, Efficient data parallel code. Triolet is a Python-syntax based
functional programming system where library implementers direct thecompiler to perform parallelization and deep optimization. Tangram is analgorithm framework that supports effective parallelization of linear
recurrence computation.

Wen-mei Hwu
Professor and Sanders-AMD
Chair, ECE
University of Illinois at UrbanaChampaign
Fighting HIV with GPUAccelerated PetascaleComputing

Molecular dynamics simulations provide a powerful tool for probing the
dynamics of cellular processes at atomic and nanosecond resolution notachievable by experimental methods alone. We describe how GPUaccelerated petascale supercomputers are enabling studies of large
biomolecular systems such as the HIV virus in all-atom detail for the first time.

2:30 PM – 3:00 PM
John Stone
Senior Research Programmer,
Associate Director, CUDA Centerof Excellence
Theoretical and Computational
Biophysics Group, Beckman
Institute for Advanced Scienceand Technology, University of
Illinois at Urbana-Champaign* Information subject to change. All times listed in Mountain Time Zone (GMT-7)

Flying Snakes on GPUs

3:00 PM – 3:30 PM
Lorena Barba
Associate Professor ofEngineering and Applied
Science
Department of Mechanical andAerospace Engineering
The George Washington
University
Exploring Emerging
Technologies in the HPC CoDesign Space
4:00 PM – 4:30 PM

It would be hard to put a flying snake in a wind tunnel. So we are trying to put
them in GPUs instead—via computational fluid dynamics. Our initial success is
to see that a flying snake's cross-section can in fact create quite some lift: iteven has a favorite angle of attack for which it gives extra lift. We don't know if
this is the secret of flying snakes, but we do know that looking at nature canteach engineers some new tricks.

New architectures, such as novel heterogeneous cores and NV-RAM memory
systems, are often radically different from today’s systems. Our team hasrecently developed a number of techniques for modeling, simulating, andmeasuring these future systems. Aspen, our performance modeling language,
allows users to compose and answer modeling questions quickly.

Jeff Vetter
Future Technologies Group
Leader and Professor
Oak Ridge National Laboratory
and Georgia Tech
Using a Hybrid Cray
Supercomputer to Model NonIcing Surfaces for Cold-Climate
Wind Turbines

We have been awarded 80 million CPU hours on Titan, a hybrid Cray
supercomputer, to model the freezing behavior of water droplets. By optimizing
the three-body mW water potential in LAMMPS, we have achieved 5x
acceleration in the hybrid CPU/GPU environment, relative to previous Jaguar
performance.

5:00 PM – 5:30 PM
Masako Yamada
Physicist
Advanced Computing Lab
GE Global Research* Information subject to change. All times listed in Mountain Time Zone (GMT-7)

20 Petaflops Simulation ofProtein Suspensions in
Crowding Conditions
5:30 PM – 6:00 PM
Simone Melchionna
Researcher
IPCF - National Research Councilof ItalyThis talk describes the recent simulation of ~18,000 proteins in suspension,
reproducing the crowding conditions of the cell interior. The simulations wereobtained with MUPHY, a computational platform for multi-scale simulations ofreal-life biofluidic problems. The same software has been used in the past to
simulate blood flows through the human coronary arteries and DNA
translocation across nanopores. The simulations were performed on the Titan
system at the Oak Ridge National Laboratory, and exhibits excellent scalability
up to 18, 000 K20X NVIDIA GPUs, reaching 20 Petaflops of aggregate sustained
performance with a peak performance of 27.5 Petaflops for the most intensive
computing component. In this talk I will describe how the combination of novel
mathematical models, computational algorithms, hardware technology andparallelization techniques allowed reproducing for the first time such a massive
amount of proteins.
ACM Gordon Bell Finalist

Wednesday, November 20 | Booth #613

Skin-Barrier Investigation Using
GPU-Enhanced Molecular
Dynamics
10:30 AM – 11:00 AM

GPU enabled molecular dynamics are being used to investigate permanentcrossing of the primary skin barrier, the stratum corneum (SC). This work is
helping to identify the molecular characteristics that dictate the ability of acompound to cross the SC barrier in order to build more accurate skinpenetration models.

Russell Devane
Scientist
Proctor & Gamble
Emerging Technologies forHigh-Performance Computing

11:00 AM – 11:30 AM
Jack Dongarra
Professor
University of Tennessee
New Features in CUDA 6 Make
GPU Acceleration Easier

11:30 AM – 12 Noon

This talk will highlight the emerging technologies in high performancecomputing. We will look at the development of accelerators and some of theaccomplishments in the Matrix Algebra on GPU and Multicore Architectures(MAGMA) project. We use a hybridization methodology that is built on
representing linear algebra algorithms as collections of tasks and data
dependencies, as well as properly scheduling the tasks' execution over theavailable multicore and GPU hardware components.

The performance and efficiency of CUDA, combined with a thriving ecosystemof programming languages, libraries, tools, training, and services, have helped
make GPU computing a leading HPC technology. Learn how powerful newfeatures in CUDA 6 make GPU computing easier than ever, helping you
accelerate more of your application with much less code.

Mark Harris
Chief Technologist, GPU
Computing
NVIDIA* Information subject to change. All times listed in Mountain Time Zone (GMT-7)

Applications of Programming
the GPU Directly from Python
Using NumbaPro
12 Noon – 12:30 PM

NumbaPro is a powerful compiler that takes high-level Python code directly to
the GPU producing fast-code that is the equivalent of programming in a lowerlevel language. It contains an implementation of CUDA Python as well as
higher-level constructs that make it easy to map array-oriented code to theparallel architecture of the GPU.

Travis OliphantCo-Founder and CEO
Continuum Analytics
Twinkle, Twinkle Little Star Using 18.000 GPUs to Simulate
Jets in the Cosmos

12:30 PM – 1:00 PM
Michael Bussmann
Junior Group Leader
Computational Radiation
PhysicsHelmholtz-Zentrum DresdenRossendorf
AMR Based on Space-Filling
Curve for Stencil Applications
1:00 PM – 1:30 PM

In order to understand what happens when jets of hot, streaming gas areejected at high speed into the cosmos, we are bound to rely on measuring theradiation emitted by the particles in the jet. Astrophysical jets can originate
from a variety of sources such as stars, black holes and even galaxies. In such
jets, the plasma flow can become unstable, generating characteristic patternsof particle flows. Using our particle-in-cell code PIConGPU utilizing thecomplete TITAN supercomputer system at Oak Ridge National Laboratory, wewere able, for the first time, to not only simulate the particle dynamics but
also the radiation emitted during the formation of such an instability, theKelvin-Helmholtz instability.
ACM Gordon Bell Finalist

AMR is an efficient method to assign a mesh with a proper resolution to any
local areas. By using bigger leaves than those of CPU, we can assign a CUDA
block to a leaf with enough thread numbers. We show a GPU implementationin which the leaves are connected by a space-filling curve.

Takayuki Aoki
Professor/Deputy Director
Global Scientific Information
and Computing Center (GSIC)/
Tokyo Institute of Technology
Can You Really Learn To Use
Accelerators in One Morning?
1:30 PM – 2:00 PM

OpenACC provides a friendly learning curve for using GPUs and otheraccelerators. We describe how we have been able to create hundreds ofcapable new users with half-day and two-day hands-on workshops. Comeknowing nothing about accelerators, leave knowing how you and yourcolleagues can get in on this important new paradigm.

John Urbanic
Information Technology
Manager
Pittsburgh Supercomputing
Center* Information subject to change. All times listed in Mountain Time Zone (GMT-7)

Tomorrow's Exascale Systems:
Not Just Bigger Versions ofToday's Peta-Computers
2:00 PM – 2:30 PM
Thomas Sterling
Executive Associate Director &Chief Scientist
Indiana University
Piz Daint: A Productive, Energy
Efficient Supercomputer with
Hybrid CPU-GPU Nodes
2:30 PM – 3:00 PM

To get to Exascale is going to require more innovation than simply extending
Petaflops machine structures with Moore’s Law. Power, reliability, user
productivity, generality, and cost all demand dramatic advances in all aspectsof supercomputer design, operation, and programming. A new synergy ofdynamic adaptive techniques, architecture, and programming interfaces are
driving research towards a new generation of HPC. This talk will introduce
these emerging ideas and illustrate how they will impact the future of ourfield.

Piz Daint: a productive, energy efficient supercomputer with hybrid CPU-GPU
nodes We will discuss the makings of Piz Daint, a Cray XC30 supercomputerwith hybrid CPU-GPU nodes. The presentation will focus on quantitative
improvements in time and energy to solution due to the use of GPU
technology in full climate, materials science and chemistry simulations.

Thomas Schulthess
Professor of Computational
Physics & Directors CSCSETH Zurich, Swiss National
Supercomputing Center (CSCS)
Deploying Clusters withNVIDIA® Tesla® GPUs

Tips and techniques for deploying high-performance computing clusters using
NVIDIA® Tesla® GPUs.

3:30 PM – 4:00 PM
Dale Southard
Senior Solution Architect
HPC/Cloud
NVIDIA
Pinning Down the
Superconducting Transition
Temperature in the Hubbard
ModelWith massive improvement in algorithms and how they map onto modern
hardware platforms, as wells as availability of efficient multi-petaflops
supercomputers like Titan, simulation-based solution of one the most sought
after problems in condensed matter theory has become possible. Implications
on studies of high-temperature superconductivity will be discussed.

4:00 PM – 4:30 PM
ACM Gordon Bell Finalist
Peter Staar
PhD Student
ETH Zurich* Information subject to change. All times listed in Mountain Time Zone (GMT-7)

The NVIDIA Co-Design Lab for
Hybrid Multicore Computing at
ETH
4:30 PM – 5:00 PM

Developing successful scientific software becomes increasingly a collaborative
endeavor, joining the talents of from a multitude of disciplines. NVIDIA andETH Zurich are forming a Co-Design Lab for Hybrid Multicore Computing as a
joint effort to develop and optimize scientific applications for hybrid
computing architectures. In this talk, I will introduce the lab and present someearly successes of this new collaboration.

Peter Messmer
Professor of Computational
Physics & Directors CSCS
NVIDIAPARALUTION - Library for
Iterative Sparse Methods on
Multi-core CPU and GPU
Devices

PARALUTION is a library which enables you to perform various sparse iterativesolvers and preconditioners on multi/many-core CPU and GPU devices. Basedon C++, it provides generic and flexible design which allows seamlessintegration with other scientific software packages, and gives you full
portability of your code.

5:00 PM – 5:30 PM
Dimitar Lukarski
Post-Doctoral Researcher
Dept. of Information
Technology, Div. of Scientific
Computing
Uppsala University
Common Use Cases andPerformance for NVAMG: A
Fast Linear Solver Toolkit on
the GPU
5:30 PM – 6:00 PM

We discuss some of common use cases for NVAMG, our toolkit for fast linear
solvers on the GPU. NVAMG includes Algebraic Multi-Grid methods, Krylov
methods, nesting preconditioners, and allows complex composition of thesolvers and preconditioners. We also present some recent performance
results on NVIDIA® Tesla® K20 and K40 GPUs for large-scale CFD problems ofindustrial relevance.

Joe Eaton
Manager, NVAMG CUDA Library
NVIDIA

Thursday, November 21 | Booth #613

From Brain Research to HighEnergy Physics: GPU-Accelerated
Applications in Jülich
11:00 AM – 11:30 AM

In 2012 the NVIDIA Application Lab at Jülich has been established to workwith application developers on GPU enablement. In this talk we will tour
through a variety of applications and evaluate opportunities of new GPU
architectures and GPU-accelerated HPC systems, in particular for dataintensive applications.

Dirk Pleiter
Leading Scientist
Jülich Supercomputing Centre* Information subject to change. All times listed in Mountain Time Zone (GMT-7)

Accessing New NVIDIA® CUDA®
Features from CUDA Fortran
11:30 AM – 12 Noon
Brent Leback
Compiler Engineering Manager
The Portland Group, NVIDIA
Earthquake Simulations withAWP-ODC on Titan, Blue Waters
and Keeneland
12 Noon – 12:30 PM

This talk will present examples of how to take advantage of new CUDA
features, specifically those introduced in CUDA 5.0 and CUDA 5.5, from CUDA
Fortran. Details of overloading one specific Fortran intrinsic function whichobtains near peak performance will be given. A preview of CUDA 6.0 featuresand how CUDA Fortran will evolve to enable them for Fortran programmers
will also be shown.

We simulate realistic 0-10 Hz earthquake ground motions relevant to building
engineering design, and accelerate SCEC CyberShake key strain tensor
calculations on Titan and Blue Waters. Performance improvements of AWPODC, coupled with co-scheduling CPUs and GPUs, make a California statewide
seismic hazard model a goal reachable with existing supercomputers.

Yifeng Cui
Lab Director, HPGeoC
San Diego Supercomputer
Center/UC San Diego
Running the FIM and NIM
Weather Models on the Titan
Supercomputer

Session description to come.

12:30 PM – 1:00 PM
Mark Govett
Chief, Advanced Computing
SectionNOAA Earth System ResearchLaboratory
HACC: Extreme Scaling and
Performance AcrossArchitectures
1:00 PM – 1:30 PM
Salman Habib
Senior Scientist
Argonne National Laboratory

Cosmological simulations of the evolution of structure in the universe areamong the most challenging of supercomputing tasks. Running on Titan, we
use HACC (Hardware/Hybrid Accelerated Cosmology Code) to demonstrate
how the use of GPUs to accelerate the force evaluations can lead tosignificantly improved performance.
ACM Gordon Bell Finalist* Information subject to change. All times listed in Mountain Time Zone (GMT-7)

New Features in NVIDIA®
CUDA® 6 Make GPU
Acceleration Easier
1:30 PM – 2:00 PM

The performance and efficiency of CUDA, combined with a thriving ecosystemof programming languages, libraries, tools, training, and services, have helped
make GPU computing a leading HPC technology. Learn how powerful newfeatures in CUDA 6 make GPU computing easier than ever, helping you
accelerate more of your application with much less code.

Mark Harris
Chief Technologist GPU
Computing
NVIDIA* Information subject to change. All times listed in Mountain Time Zone (GMT-7)