Held in conjunction with SC'14

Description
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With Exascale systems on the horizon, we will be ushering in an era with power
and energy consumption as the primary concerns for scalable computing. To
achieve viable high performance, revolutionary methods are required with a
stronger integration among hardware features, system software and applications.
Equally important are the capabilities for fine-grained spatial and temporal
measurement and control to facilitate energy efficient computing across
all layers. Current approaches for energy efficient computing rely heavily on
power efficient hardware in isolation. However, it is pivotal for hardware to
expose mechanisms for energy efficiency to optimize power and energy
consumption for various workloads and to reduce data motion, a major component
of energy use. At the same time, high fidelity measurement techniques,
typically ignored in data-center level measurement, are of high importance
for scalable and energy efficient inter-play in different layers of
application, system software and hardware.

This workshop seeks to address the important energy efficiency aspects in the
HPC community that have not been previously addressed by aspects covered in
the data center or cloud computing communities. Emphasis is given to the
applications view related to significant energy efficiency improvements and
to the required hardware/software stack that must include necessary power and
performance measurement and analysis harnesses.

Current tools are often limited by hardware capabilities and their lack of
information about the characteristics of a given workload/application. In the
same manner, hardware techniques, like dynamic voltage frequency scaling, are
often limited by their granularity (very coarse power management) or by their
scope (a very limited system view). More rapid realization of energy savings
will require significant increases in measurement resolution and optimization
techniques. Moreover, the interplay between performance, power and
reliability add another layer of complexity to this already difficult group
of challenges.


Workshop Focus
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We encourage submissions in the following areas:

- Tools for analyzing power and energy with different granularities and
scope from hardware (e.g., component, core, node, rack, system) or
software views (e.g., threads, tasks, processes, etc.) or both.
- Tools and techniques for measurement, analysis, and modeling of thermal
effects at different granularities (e.g., component, core, node, rack,
system) for large-scale systems.
- Techniques that enable power and energy optimizations at different
scale levels for HPC systems.
- Integration of power-aware technologies in applications and throughout
the software stack of HPC systems.
- Characterization of current state-of-the-art HPC systems and
applications in terms of power.
- Disruptive hardware of infrastructure technologies for energy-efficient
supercomputing.
- Analysis of future technologies that will provide improved energy
consumption and management on future HPC systems.


Organizing Committee
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General Chairs: Kirk Cameron, Virginia Tech, USA
Adolfy Hoisie, Pacific Northwest National Laboratory, USA
Darren Kerbyson, Pacific Northwest National Laboratory, USA
David Lowenthal, Arizona State University, USA
Dimitrios S. Nikolopoulos, Queen's University of Belfast, UK
Sudha Yalamanchili, Georgia Institute of Technology, USA
Program Chair: Andres Marquez, Pacific Northwest National Laboratory, USA
Publicity Chair: Kevin J. Barker, Pacific Northwest National Laboratory, USA
European Liaison: Michele Weiland, EPCC, UK
Publication Chair: Abhinav Vishnu, Pacific Northwest National Laboratory, USA
Onsite Coordination: Joseph Manzano, Pacific Northwest National Laboratory, USA


Program Committee
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Avram Bar-Cohen DARPA-MTO, USA
Laura Carrington San Diego Supercomputing Center, USA
Sunita Chandrasekaran University of Houston, USA
Paul Franzon North Carolina State University, USA
Roberto Gioiosa Pacific Northwest National Laboratory, USA
Georg Hager Erlangen Regional Computing Center, Germany
Karen Karavanic Portland State University, USA
Hyesoon Kim Georgia Institute of Technology, USA
Dong Li Oak Ridge National Laboratory, USA
Sheng Li Intel, USA
Benoit Meister Reservoir Labs, USA
Leonid Oliker Lawrence Berkeley National Laboratory, USA
Barry Rountree Lawrence Livermore National Laboratory, USA
Vijay Reddi University of Texas at Austin, USA
Sameer Shende University of Oregon, USA
Shuaiwen Leon Song Pacific Northwest National Laboratory, USA
Eric Van Hensbergen ARM Research, USA