[Apologies for cross-posting.]
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***** 4th Workshop on Big Data Benchmarking *****
http://clds.sdsc.edu/wbdb2013.us

*** October 09-10, 2013 ***
*** Brocade Executive Briefing Center, San Jose, CA, USA ***
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Workshop Description
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The objective of this workshop is to explore issues in developing
industry-standard benchmarks for providing objective measures of
the effectiveness of hardware and software systems for big data
applications. While micro-benchmarks and functional benchmarks,
such as Terasort, play an important role, the workshop is especially
interested in application-level, end-to-end benchmarks. A successful
benchmark would be simple to implement and execute; cost effective,
so that the benefits of executing the benchmark justify its expense;
timely, with benchmark versions keeping pace with rapid changes in
the marketplace; and verifiable so that results of the benchmark can
be validated via independent means. Previous, independent workshops
on this topic have led to the development of two benchmark proposals:
one based on a Deep Analytics Pipeline for event processing and a
second, called BigBench, based on extending the TPC-DS benchmark with
semi-structured and unstructured data and new queries targeted at
those data.


Topics
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Related research topics explore a broad range of characteristics that
define big data and big data applications, including:

O DATA FEATURES: New feature sets of data including, high-dimensional
data, sparse data, event-based data, and enormous data sizes.
O SYSTEN CHARACTERISTICS: System-level issues including, large-scale
and evolving system configurations, shifting loads, and
heterogeneous technologies for big data and cloud platforms.
O IMPLIMENTATION OPTIONS: Different implementation options such as
SQL, NoSQL, Hadoop software ecosystem, and different
implementations of HDFS.
O WORKLOAD: Representative big data business problems and
corresponding benchmark implementations. Specifying benchmark
applications that represent different modalities of big data,
including graphs, streams, scientific data, and document
collections.
O HARDWARE OPTIONS: Evaluating new options in hardware including
different types of HDD, SSD, and main memory, and large-memory
systems, and new platform options that include dedicated commodity
clusters and cloud platforms.
O DATA GENERATION: Models and procedures for generating large-scale
synthetic data with requisite properties.
O BENCHMARK EXECUTIONS RULES, e.g. data scale factors, benchmark
versioning to account for rapidly evolving workloads and system
configurations, benchmark metrics.
O METRICS FOR EFFICIENCY: Measuring the efficiency of the solution,
e.g., based on costs of acquisition, ownership, energy and/or other
factors.
O EVALUATION FRAMEWORKS: Tool chains, suites and frameworks for
evaluating big data systems.
O EARLY IMPLEMENTATIONS of the Deep Analytics Pipeline or BigBench,
or describing lessons learned in benchmarking big data applications
are solicited. Discussions of enhancements to these benchmarks are
also encouraged, for example, including more data genres (e.g.,
graphs) in the workload; considering a range of machine learning
and other algorithms, etc. Papers proposing other benchmarking
alternatives will also be considered.


Paper Submission, Review, and Publication
-----------------------------------------
Papers should be formatted using the Springer LNCS Proceedings format.
Selected revised papers will be published in Lecture Notes in Computer
Science by Springer.

Full papers: max. 12 pages
Short papers: max. 6 pages

Please use the following submission system to submit your paper:
https://cmt.research.microsoft.com/WBDB2013/


Submission Dates:
-----------------
O September 6, 2013:
Due date for full workshop papers submission
O September 20, 2013:
Notification of paper acceptance to authors
O October 09-10, 2013:
Workshop
O October 18, 2013:
Camera-ready of accepted papers


Contact
-------
For questions please contact Chaitan Baru (baru[at]sdsc[dot]edu).


Previous instances of the workshops:
------------------------------------
O May 2012 in San Jose, CA, USA (http://clds.ucsd.edu/wbdb2012)
O December 2012 in Pune, India (http://clds.ucsd.edu/wbdb2012.in)
O July 2013 in Xi'an, China (http://clds.ucsd.edu/wbdb2013.cn)


Workshop Chair(s):
---------------
O Chaitan Baru (San Diego Supercomputer Center, UC San Diego)
O Milind Bhandarkar (Pivotal)
O Tilmann Rabl (Middleware Services Research Group, U of Toronto)

Publicity Chair(s):
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O Florian Stegmaier (University of Passau, Germany)

Programm Chair(s):
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O Dhruba Borthakur (Facebook)
O Yanpei Chen (Cloudera)
O John Galloway
O Ahmad Ghazal (Oracle)
O Boris Glavic (IIT Chicago)
O Bhasker Gowda (Intel)
O Eyal Gutkind (Mellanox)
O Songlin Hu (Chinese Academy of Science)
O Jian Li (IBM)
O DK Panda (Ohio State University)
O Scott Pearson (Brocade)
O Meikel Poess (Oracle)
O Francois Raab (InfoSizing)
O Kai Sachs (SAP)
O Jerry Zhao (Google)
O Jianfeng Zhan (Chinese Academy of Sciences)