[AISWorld] CFP: International Workshop on Hardware Accelerated Data Mining at ICDM 2015

Wenjun Zhou wzhou7 at gmail.com
Mon Jul 13 16:24:04 EDT 2015


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
- 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, and streaming data
- Domain-Specific Languages for hardware synthesis of data mining
- Novel data mining algorithms optimized for massively parallel
- 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).


Organization Chairs

Charalampos Chelmis, University of Southern California, USA; Anand
Panangadan, University of Southern California, USA

Technical 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

Wenjun Zhou, Assistant Professor
Business Analytics and Statistics
Haslam College of Business
University of Tennessee Knoxville

Address: 916 Volunteer Blvd., Room SMC 247, Knoxville, TN 37996-0532
Phone: (865) 974-9198
Email: wzhou4 at utk.edu or wzhou7 at gmail.com
Homepage: http://web.utk.edu/~wzhou4/

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