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SC10
Guy Tel-Zur
November 2010

My Own Diary
• A subjective impression from SC10

Outline
• The Tutorials
• Plenary Talks
• Papers & Panels
• The Top500 list
• The Exhibition
http://sc10.supercomputing.org/

Day 0 - Arrival
US Airways entertainment system is
running Linux!

A lecture by Prof. Rubin Landau
Computational Physics at the
Educational Track
3:30PM - 5:00PM Communities, Education Physics: Examples in Computational
Physics, Part 2 Physics: Examples in Computational Physics, Part 2 Rubin Landau 297
Although physics faculty are incorporating computers to enhance physics education,
computation is often viewed as a black box whose inner workings need not be
understood. We propose to open up the computational black box by providing
Computational Physics (CP) curricula materials based on a problem-solving paradigm that
can be incorporated into existing physics classes, or used in stand-alone CP classes. The
curricula materials assume a computational science point of view, where understanding of
the applied math and the CS is also important, and usually involve a compiled language in
order for the students to get closer to the algorithms. The materials derive from a new CP
eTextbook available from Compadre that includes video-based lectures, programs, applets,
visualizations and animations.

Eclipse PTP
At last FORTRAN has an
advanced, free, IDE !!!
PTP - Parallel Tools Platform
http://www.eclipse.org/ptp/

Python for Scientific Computing

Amazon Cluster GPU Instances provide 22 GB of memory, 33.5 EC2 Compute
Units, and utilize the Amazon EC2 Cluster network, which provides high throughput
and low latency for High Performance Computing (HPC) and data intensive
applications. Each GPU instance features two NVIDIA Tesla® M2050 GPUs,
delivering peak performance of more than one trillion double-precision FLOPS.
Many workloads can be greatly accelerated by taking advantage of the parallel
processing power of hundreds of cores in the new GPU instances. Many industries
including oil and gas exploration, graphics rendering and engineering design are
using GPU processors to improve the performance of their critical applications.
Amazon Cluster GPU Instances extend the options for running HPC workloads in
the AWS cloud. Cluster Compute Instances, launched earlier this year, provide the
ability to create clusters of instances connected by a low latency, high throughput
network. Cluster GPU Instances give customers with HPC workloads an additional
option to further customize their high performance clusters in the cloud. For those
customers who have applications that can benefit from the parallel computing
power of GPUs, Amazon Cluster GPU Instances can often lead to even further
efficiency gains over what can be achieved with traditional processors. By
leveraging both instance types, HPC customers can tailor their compute cluster to
best meet the performance needs of their workloads. For more information on HPC
capabilities provided by Amazon EC2, visit aws.amazon.com/ec2/hpc-applications.
Amazon Cluster GPU Instances

World’s #1
China's National University of Defense Technology's Tianhe-1A
supercomputer has taken the top ranking from Oak Ridge National
Laboratory's Jaguar supercomputer on the latest Top500 ranking of
the world's fastest supercomputers. The Tianhe-1A achieved a
performance level of 2.67 petaflops per second, while Jaguar
achieved 1.75 petaflops per second. The Nebulae, another Chinese-
built supercomputer, came in third with a performance of 1.27
petaflops per second. "What the Chinese have done is they're
exploiting the power of [graphics processing units], which
are...awfully close to being uniquely suited to this particular
benchmark," says University of Illinois Urbana-Champagne
professor Bill Gropp. Tianhe-1A is a Linux computer built from
components from Intel and NVIDIA. "What we should be focusing on
is not losing our leadership and being able to apply computing to a
broad range of science and engineering problems," Gropp says.
Overall, China had five supercomputers ranked in the top 100, while
42 of the top 100 computers were U.S. systems.

http://www.green500.org

SC10 Keynote Lecture
Clayton M. Christensen - Harvard Business School

Disruption is the mechanism by which great companies continue to succeed and new
entrants displace the market leaders. Disruptive innovations either create new markets or
reshape existing markets by delivering relatively simple, convenient, low cost innovations to
a set of customers who are ignored by industry leaders. One of the bedrock principles of
Christensen's disruptive innovation theory is that companies innovate faster than
customers' lives change. Because of this, most organizations end up producing products
that are too good, too expensive, and too inconvenient for many customers. By only
pursuing these "sustaining" innovations, companies unwittingly open the door to "disruptive"
innovations, be it "low-end disruption" targeting overshot-less-demanding customers or
"new-market disruption", targeting non-consumers. 1. Many of today’s markets that appear
to have little growth remaining, actually have great growth potential through disruptive
innovations that transform complicated, expensive products into simple, affordable ones. 2.
Successful innovation seems unpredictable because innovators rely excessively on data,
which is only available about the past. They have not been equipped with sound theories
that do not allow them to see the future perceptively. This problem has been solved. 3.
Understanding the customer is the wrong unit of analysis for successful innovation.
Understanding the job that the customer is trying to do is the key. 4. Many innovations
that have extraordinary growth potential fail, not because of the product or service itself, but
because the company forced it into an inappropriate business model instead of creating a
new optimal one. 5. Companies with disruptive products and business models are the ones
whose share prices increase faster than the market over sustained periods
How to Create New Growth in a Risk-
Minimizing Environment

High-End Computing and Climate
Modeling: Future Trends and Prospects
SESSION: Big Science, Big Data II
Presenter(s):Phillip Colella
ABSTRACT:
Over the past few years, there has been considerable discussion of the change in
high-end computing, due to the change in the way increased processor performance
will be obtained: heterogeneous processors with more cores per chip, deeper and
more complex memory and communications hierarchies, and fewer bytes per flop.
At the same time, the aggregate floating-point performance at the high end will
continue to increase, to the point that we can expect exascale machines by the
end of the decade. In this talk, we will discuss some of the consequences of these
trends for scientific applications from a mathematical algorithm and software
standpoint. We will use the specific example of climate modeling as a focus, based
on discussions that have been going on in that community for the past two years.
Chair/Presenter Details:
Patricia Kovatch (Chair) - University of Tennessee, Knoxville
Phillip Colella - Lawrence Berkeley National Laboratory

Prediction of Earthquake Ground Motions
Using Large-Scale Numerical Simulations
SESSION: Big Science, Big Data II
Presenter(s):Tom Jordan
ABSTRACT:
Realistic earthquake simulations can now predict strong ground motions from
the largest anticipated fault ruptures. Olsen et al. (this meeting) have simulated
a M8 “wall-to-wall” earthquake on southern San Andreas fault up to 2-Hz,
sustaining 220 teraflops for 24 hours on 223K cores of NCCS Jaguar. Large
simulation ensembles (~10^6) have been combined with probabilistic rupture
forecasts to create CyberShake, a physics-based hazard model for Southern
California. In the highly-populated sedimentary basins, CyberShake predicts
long-period shaking intensities substantially higher than empirical models,
primarily due to the strong coupling between rupture directivity and basin
excitation. Simulations are improving operational earthquake forecasting, which
provides short-term earthquake probabilities using seismic triggering models,
and earthquake early warning, which attempts to predict imminent shaking
during an event. These applications offer new and urgent computational
challenges, including requirements for robust, on-demand supercomputing
and rapid access to very large data sets.

Exascale Computing Will (Won't) Be Used
by Scientists by the End of This Decade
EVENT TYPE: Panel
Panelists:Marc Snir, William Gropp, Peter Kogge, Burton Smith, Horst Simon, Bob
Lucas, Allan Snavely, Steve Wallach
ABSTRACT:
DOE has set a goal of Exascale performance by 2018. While not impossible, this
will require radical innovations. A contrarian view may hold that technical obstacles,
cost, limited need, and inadequate policies will delay exascale well beyond 2018.
The magnitude of the required investments will lead to a public discussion for which
we need to be well prepared. We propose to have a public debate on the
proposition "Exascale computing will be used by the end of the decade", with one
team arguing in favor and another team arguing against. The arguments should
consider technical and non-technical obstacles and use cases. The proposed
format is: (a) introductory statements by each team (b) Q&A's where each team can
put questions to other team (c) Q&A's from the public to either teams. We shall
push to have a lively debate that is not only informative, but also entertaining.

GPU Computing: To ExaScale and
Beyond
Bill Dally - NVIDIA/Stanford University

Dedicated High-End Computing to Revolutionize
Climate Modeling: An International Collaboration
ABSTRACT:
A collaboration of six institutions on three continents is investigating the use of
dedicated HPC resources for global climate modeling. Two types of
experiments were run using the entire 18,048-core Cray XT-4 at NICS from
October 2009 to March 2010: (1) an experimental version of the ECMWF
Integrated Forecast System, run at several resolutions down to 10 km grid
spacing to evaluate high-impact and extreme events; and (2) the NICAM global
atmospheric model from JAMSTEC, run at 7 km grid resolution to simulate the
boreal summer climate, over many years. The numerical experiments sought to
determine whether increasing weather and climate model resolution to
accurately resolve mesoscale phenomena in the atmosphere can improve the
model fidelity in simulating the mean climate and the distribution of variances
and covariances.
Chair/Presenter Details:
Robert Jacob (Chair) - Argonne National Laboratory
James Kinter - Institute of Global Environment and Society

Using GPUs for Weather and Climate Models
Presenter(s):Mark Govett
ABSTRACT:
With the power, cooling, space, and performance restrictions facing large CPU-
based systems, graphics processing units (GPUs) appear poised to become
the next-generation super-computers. GPU-based systems already are two of
the top ten fastest supercomputers on the Top500 list, with the potential to
dominate this list in the future. While the hardware is highly scalable, achieving
good parallel performance can be challenging. Language translation, code
conversion and adaption, and performance optimization will be required. This
presentation will survey existing efforts to use GPUs for weather and climate
applications. Two general parallelization approaches will be discussed. The
most common approach is to run select routines on the GPU but requires
data transfers between CPU and GPU. Another approach is to run
everything on the GPU and avoid the data transfers, but this can require
significant effort to parallelize and optimize the code.

Global Arrays
Global Arrays Roadmap and Future Developments
SESSION: Global Arrays: Past, Present & Future
EVENT TYPE: Special and Invited Events
SESSION CHAIR: Moe Khaleel
Speaker(s):Daniel Chavarria
ABSTRACT:
This talk will describe the current state of the Global Arrays toolkit and its
underlying ARMCI communication layer and how we believe they should
evolve over the next few years. The research and development agenda is
targeting expected architectural features and configurations on emerging
extreme-scale and exascale systems.
Speaker Details:
Moe Khaleel (Chair) - Pacific Northwest National Laboratory
Daniel Chavarria - Pacific Northwest National Laboratory

http://www.emsl.pnl.gov/docs/global/

Enabling High Performance Cloud
Computing Environments
SESSION LEADER(S):Jurrie Van Den Breekel
ABSTRACT:
The cloud is the new “killer” service to bring service providers and enterprises into the
age of network services capable of infinite scale. As an example, 5,000 servers with
many cloud services could feasibly serve one billion users or end devices. The idea of
services at this scale is now possible with multi-core processing, virtualization and high
speed Ethernet, but even today the mix of implementing these technologies requires
careful considerations in public and private infrastructure design. While cloud computing
offers tremendous possibilities, it is critical to understanding the limitations of this
framework across key network attributes such as performance, security, availability and
scalability. Real-world testing of a cloud computing environment is a key step toward
putting any concerns to rest around performance, security and availability. Spirent will
share key findings that are the result of some recent work with the European Advanced
Networking Test Center (EANTC) including a close examination of how implementing a
cloud approach within a private or private data center affects the firewall, data center
bridging, virtualization, and WAN optimization.
Session Leader Details:
Jurrie Van Den Breekel (Primary Session Leader) - Spirent Communications

Cont’
Speakers:
NEOVISE – Paul Burns
SPIRENT – Jurrie van den Breekel
BROCADE – Steve Smith
Paul:
Single application – single server
Single application – multiple servers (cluster computing)
Multiple applications – single sever – virtualization
Multiple applications – multiple servers – Cloud computing
3rd dimension : tenants, T1 T2 on the same physical server - security

Future Supercomputing Centers
Thom Dunning, William Gropp, Thomas Lippert, Satoshi Matsuoka, Thomas
Zacharia
This panel will discuss the nature of federal- and state-supported
supercomputing centers, what is required to sustain them in the future, and
how they will cope with the evolution of computing technology. Since the
federally supported centers were created in the mid-1980s, they have fueled
innovation and discovery, increasing the number of computational
researchers, stimulating the use of HPC in industry, and pioneering new
technologies. The future of supercomputing is exciting—sustained petascale
systems are here with planning for exascale systems now underway—but it
also challenging— disruptive technology changes will be needed to
reach the exascale. How can supercomputing help ensure that today’s
petascale supercomputer are effectively used to advance science and
engineering and how can they help the research and industrial communities
prepare for an exciting, if uncertain future?

Advanced HPC Execution Models:
Innovation or Disruption
Panelists:Thomas L. Sterling, William Carlson, Guang Gao, William Gropp, Vivek
Sarkar, Thomas Sterling, Kathy Yelick
ABSTRACT:
An execution model is the underlying conceptual foundation that integrates the
HPC system architecture, programming methods, and intervening Operating
System and runtime system software. It is a set of governing principles that govern
the co-design, operation, and interoperability of the system layers to achieve most
efficient scalable computing in terms of time and energy. Historically, HPC has been
driven by five previous epochs of execution models including the most recent CSP
that has been exemplified by "Pax MPI" for almost two decades. HPC is now
confronted by a severe barrier of parallelism, power, clock rate, and complexity
exemplified by multicore and GPU heterogeneity impeding progress between
today's Petascale and the end of the decade's Exascale performance. The panel
will address the key questions of requirements, form, impact, and programming of
such future execution models should they emerge from research in academia,
industry, and government centers.

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