[hpc-announce] NDM'15: November 16, 2015 - Network-aware Data Management: ACM SIGHPC, IEEE/ACM SC'15 workshop

[Mehmet Balman]

Apologies if you got multiple copies of this email. Please circulate
this Call for Participation among your colleagues.
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 The 5th International Workshop on Network-aware Data Management
(NDM'15) in cooperation with ACM SIGHPC,
in conjunction with SC15: IEEE/ACM International Conference for High
Performance Computing, Networking, Storage and Analysis, in Austin,
Texas, USA.

Website: http://ndm-meeting.org
Date: November 16, 2015 (2:00pm-5:30pm)
Location: Hilton 410
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* Program

2:00-2:05 Opening Remarks

2:05-2:35 Keynote Speech
Network Integration with Workload Management - the PanDA Example
Kaushik De (University of Texas at Arlington)

2:35-3:00
Managing Scientific Data with Named Data Networking (NDN)
Susmit Shannigrahi (Colorado State University)

3:00-3:30 Coffee Break

3:30-3:55
A Multi-domain SDN for Dynamic Layer-2 Path Service
Fatma AL-Ali (University of Virginia)

3:55-4:20
Design and Implementation of Control Sequence Generator for SDN-enhanced MPI
Baatarsuren Munkhdorj (Osaka University)

4:20-4:45
Approximate Causal Consistency for Partially Replicated Geo-Replicated
Cloud Storage
Tayuan    Hsu (University of Illinois at Chicago)

4:45-5:10
Hysteresis-based Optimization of Data Transfer Throughput
Md S Q Zulkar    Nine (University at Buffalo (SUNY)

5:10-5:30   Closing Remarks

* Registration:

Please visit http://sc15.supercomputing.org/register for more information.

Workshop-Only Fees:
Attendees can register workshops independent of the technical program.
Workshop only registration is $200 ($100 for students)

Workshop Fees with Technical Program Registration:
SC14 technical program attendees receive a reduced rate of $90 ($40
for students) for workshop registration.

* Scope:

Today’s data centric environment both in industry and scientific
domains depends on the underlying network infrastructure and its
performance, to deliver highly distributed extreme-scale application
workloads. As current technology enables faster storage devices and
larger interconnect bandwidth, there is a substantial need for novel
system design and middleware architecture to address increasing
latency and scalability requirements. Furthermore, limitations in
end-system architecture and system software design play an important
role in many-core platforms. Traditional network and data management
techniques are unlikely to scale to meet the needs of future
data-intensive systems. We require new collaborations between data
management and networking communities to develop intelligent
networking middleware and efficient data management infrastructure.
This workshop seeks contributions from academia, government, and
industry to discuss future design principles of network-aware data
management. We focus on emerging trends in resource coordination,
data-aware scheduling, storage technologies, end-to-end performance,
network-aware workflow management, high-performance networking, and
network virtualization.

 * Workshop Organizers:
         Mehmet Balman, VMware, Inc. & Lawrence Berkeley National Laboratory
         Surendra Byna, Lawrence Berkeley National Laboratory
         Brian L. Tierney, Energy Sciences Network (ESnet) & Lawrence
Berkeley National Laboratory

 * Program Committee:
Pavan Balaji, Argonne National Laboratory and Northwestern University, USA
Jerry Chou, National Tsing Hua University, Taiwan
Constantine Dovrolis, Georgia Institute of Technology, USA
Zhihui Du, Tsinghua University, China
Renato J Figueiredo, University of Florida, USA
Kartik Gopalan, State University of New York at Binghamton, USA
Zhiyi Huang, University of Otago, New Zealand
Raj Kettimuthu, Argonne National Laboratory and University of Chicago, USA
Jinoh Kim, Texas A&M University-Commerce, USA
Siva Kulasekaran, Texas Advanced Computing Center, USA
Manish Parashar, Rutgers University, USA
Eric Pouyoul, Energy Sciences Network and Lawrence Berkeley Lab, USA
Yusuke Tanimura, National Institute of Advanced Industrial Science and
Technology, Japan
Malathi Veeraraghavan, University of Virginia, USA
Venkat Vishwanath, Argonne National Laboratory, USA
Chen Wu, ICRAR, The University of Western Australia, Australia
Wenji Wu, Fermilab, USA
Lei Xia, LinkedIn, USA
Esma Yildirim, Fatih University, Turkey
Michelle M. Zhu, Southern Illinois University, USA
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