GTC 2012 Program Guide - GPU Technology Conference

TUESDAY
TUESDAY, MAY 15, 17:00 (50 MINUTES)
HALL 1
S0156 Towards Computing the Cure for Cancer
Attend this session to learn about how to create “designer”
genomic analysis pipelines as part of the “Compute the Cure” for
cancer initiative from NVIDIA Foundation. It will offer an overview
of an open-source framework that enables the creation of
customized genomic analysis pipelines. It will disucss how
different plug-ins from the “mapping/realignment/discovery”
repositories, respectively, can be composed to form a genomic
analysis pipeline. Attendees will learn to use next-generation
sequencing data to characterize previously undetectable genetic
changes between normal and malignant cells and ways to
contribute to the “Compute the Cure” cause.
Speaker(s): Wu Feng (Professor, Virginia Tech), Heshan Lin (Research
Scientist, Virginia Tech)
Topic(s): Bioinformatics, Life Sciences, Supercomputing, Algorithms &
Numerical Techniques (Intermediate)
TUESDAY, MAY 15, 17:00 (25 MINUTES
ROOM C
S0219 Efficient Top-Down Planning in
Business Intelligence
In business intelligence, tasks like corporate planning or what-if
analysis complement traditional reporting and analysis. One main
difference is that while the latter only read data, the former
require the change of possibly large numbers of existing and
creation of new data records in the business model, preferably in
real time. In this session, we describe the extension of an existing
BI tool, Jedox OLAP, by GPU-based parallel algorithms for
interactive planning scenarios. Compared to sequential inmemory
algorithms, our CUDA approach yields tremendous
speedups and can also cope with large amounts of data by using
multiple GPUs.
Speaker(s): Tobias Lauer (Senior Researcher, Jedox AG), Alexander
Haberstroh (Software Developer, Jedox AG)
Topic(s): Databases, Data Mining, Business Intelligence, Finance,
Algorithms & Numerical Techniques (Intermediate)
TUESDAY, MAY 15, 17:00 (50 MINUTES)
MARRIOTT BALLROOM 3
S0247 3D ADI Method for Fluid Simulation on
Multiple GPUs
Find out about a multiple GPU implementation of the Alternating
Direction Implicit method for large 3D domains. The ADI technique
is applied towards direct numerical fluid simulation. Modeling
complex flows demands extremely large grids and a distributed
computation is required for sharing the memory among multiple
GPUs. In this session a novel distributed tridiagonal solver as well
as parallelization and load balancing strategies will be covered in
detail. Finally, a comprehensive performance analysis and scaling
studies for different input geometries and possible future
improvements will be discussed.
Speaker(s): Nikolay Markovskiy (HPC DevTech Engineer, NVIDIA),
Nikolai Sakharnykh (Developer Technology Engineer, NVIDIA)
Topic(s): Algorithms & Numerical Techniques, Computational
Fluid Dynamics (Intermediate)
TUESDAY, MAY 15, 17:00 (50 MINUTES)
ROOM J2
S0267A Mixing Graphics and Compute with Multiple GPUs
In this session we will cover all the different aspects of interaction
between graphics and compute. The first part of the session will
focus on compute API interoperability with OpenGL (using CUDA
and OpenCL APIs), while the second part of the session will delve
into interoperability at a system level. In particular we will go
through the challenges and benefits of dedicating one GPU for
compute and another for graphics, how different system
configurations affect data transfer between two GPUs, and how it
translates into application design decisions helping to enable an
efficient, cross-GPU interoperability between compute and
graphics contexts.
This session is repeated on Thursday at 15:30 (S0267B).
Speaker(s): Alina Alt (Applied Engineer, NVIDIA)
Topic(s): Visualization Application Design & Porting Techniques
(Beginner)
TUESDAY, MAY 15, 17:00 (50 MINUTES)
ROOM A5
S0359 VMware and NVIDIA: Delivering 3D Workstations
from the Cloud
This session will detail the delivery of the most demanding
Workstation class workloads from the private cloud using
technologies from NVIDIA and VMware. We will cover the
configuration and performance metrics of the combined VMware,
NVIDIA direct pass through hardware accelerated graphics
solution. Using sample workloads, we will demonstrate how
customers can realize the operational and security benefits of
cloud based personal computing without sacrificing performance.
Speaker(s): Aaron Blasius (Sr. Product Manager, VMware), Warren
Ponder (Director, Product Management, VMware)
Topic(s): Visualization, Cloud Computing (Advanced)
TUESDAY, MAY 15, 17:00 (50 MINUTES)
ROOM L
S0427 Intra-Day Risk-Management with Parallelized
Algorithms on GPUs
The challenge with intra-day risk management is that a very large
number of calculations are required to be performed in a very
short amount of time. Typically, we may be interested in
calculating VaR for 100 to 1000 securities per second based on
100 million potential scenarios. The magnitude of these
calculations is not Utopian but it reflects the reality of modern
financial institutions and exchanges. In this presentation, we
outline how the complex problem of intra-day risk management
can be solved using parallelized algorithms on GPUs. The
methodology has been proven in a POC at 2 financial institutions.
Speaker(s): Partha Sen (CEO, Fuzzy Logix)
Topic(s): Databases, Data Mining, Business Intelligence, Finance,
Algorithms & Numerical Techniques, Supercomputing (Advanced)
TUESDAY, MAY 15, 17:00 (50 MINUTES)
ROOM A3
S0602 An Introduction to the Thrust Parallel
Algorithms Library
Thrust is a parallel algorithms library which resembles the C++
Standard Template Library (STL). Thrust’s high-level interface
greatly enhances developer productivity while enabling performance
portability between GPUs and multicore CPUs. Interoperability with
established technologies (such as CUDA, TBB and OpenMP)
facilitates integration with existing software. In this talk we’ll walk
though the library’s main features and explain how developers can
build high-performance applications rapidly with Thrust.