We are organizing the International Workshop on Hardware Accelerated Data
Mining, in conjunction with ICDM 2015. IEEE International Conference on
Data Mining (ICDM) is one of the world's premier research conference in
data mining. You can find more details about the workshop here.
http://volga.usc.edu/hadm/
I am including the CFP.
Regards,
Dr. Arindam Pal
Research Scientist
Innovation Labs Kolkata
TCS Research
http://www.cse.iitd.ac.in/~arindamp/
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Call for papers:
International Workshop on Hardware Accelerated Data Mining (HADM'15) to be
held with IEEE International Conference on Data Mining
14 November 2015, Atlantic City, New Jersey, USA.
Website: http://www.usc.edu/hadm
==================================================
Data mining is expected to work on increasingly complex workloads (e.g.,
Petabytes of networked-data under real-time constraints) using emerging
hardware accelerators (e.g., commodity and specialized Multi-core, GPUs,
FPGAs, and ASICs) and corresponding programming models (e.g., MapReduce,
GraphLab, CUDA, OpenCL, and OpenACC). The use of hardware accelerators for
mining high-rate data streams is becoming common mainly due to the rapidly
increasing amount of data available for real-time analytics. The idea of
using special-purpose hardware to accelerate computation has a long
tradition in data processing but has thus far not made its way into
mainstream data mining. Many essential issues in this area have yet to be
explored. For instance, large-scale graph computations are commonplace in
many fields. However, this graph data is sparse and highly non-uniform.
Graph structure mining algorithms exhibit weak spatial locality when
processing graphs with power law distributions and such algorithms are
data-intensive and cache-hostile.
The aim of this workshop is to provide a venue for designers,
practitioners, researchers, developers, and industrial/governmental
partners to come together, present and discuss leading research results,
use cases, innovative ideas, challenges, and opportunities that arise from
accelerating mining of big data using new hardware, and identify future
directions and challenges in this area.
Topics of Interest
Topics of interests include but are not limited to:
Algorithms, models, and theory of hardware accelerated data mining
Hardware accelerated data mining systems and platforms
Scalable algorithms & architectures for Machine learning over
structured, semi-structured, spatio-temporal, graph, streaming, data
Domain-Specific Languages for hardware synthesis of data mining
applications
Novel data mining algorithms optimized for massively parallel
architectures
Hardware acceleration of data mining in applications from different
domains, including social science, bioinformatics, and smart grids
Key dates:
Due date for full workshop papers: July 20, 2015 Notification of workshop
papers acceptance to authors: September 1, 2015 Camera-ready deadline for
accepted papers: September 10, 2015 Workshop date: November 14, 2015
Papers should be at most 10 pages in the IEEE 2-column format (for IEEE
Computer Society conference proceedings).
Workshop Organization
Co-chairs
Charalampos Chelmis, University of Southern California, USA
Anand Panangadan, University of Southern California, USA
Program Committee
Jaume Bacardit, Newcastle University, United Kingdom
Zachary Baker, Los Alamos National Laboratory, USA
Rajesh Bordawekar, Thomas J. Watson Research Center, USA
Sutanay Choudhury, Pacific Northwest National Laboratory, USA
Eric Chung, Microsoft Research, USA
Hadi Esmaeilzadeh, Georgia Institute of Technology, USA
Joo-Young Kim, Microsoft Research, USA
Ioannis Koltsidas, IBM Zurich Research Laboratory, Switzerland
Walid Najjar, University of California, Riverside, USA
Arindam Pal, Innovation Labs Kolkata, TCS Research, India
Ippokratis Pandis, Cloudera, USA
Edward Yi-Hua Yang, Google, Inc., USA
Yinglong Xia, IBM Thomas J. Watson Research Center, USA
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