Computing in large-scale systems is shifting away from the traditional compute-centric model successfully used for many decades into one that is much more data-centric. This transition is driven by the evolving nature of what computing comprises, no longer dominated by the execution of arithmetic and logic calculations but instead becoming dominated by large data volume and the cost of moving data to the locations where computations are performed. Data movement impacts performance, power efficiency and reliability, three fundamental components of a system. These trends are leading to changes in the computing paradigm, in particular the notion of moving computation to the data in a so-called Near-Data Processing approach, which seeks to perform computations in the most appropriate location depending on where data resides and what needs to be extracted from that data. Examples already exist in systems that perform some computations closer to disk storage, leveraging the data streaming coming from the disks, filtering the data so that only useful items are transferred for processing in other parts of the system. Conceptually, the same principle can be applied throughout a system, by placing computing resources close to where data is located, and decomposing applications so that they can leverage such a distributed and potentially heterogeneous computing infrastructure. This workshop is intended to bring together experts from academia and industry to share advances in the development of Near-Data Processing systems principles, with emphasis on large-scale systems. We expect this workshop to be the first one in an emerging area of computer architecture. The workshop will consist of submitted papers and invited talks. Topics of interest include but are not limited to

Analysis of applications illustrating the potential for Near-Data Processing
System and software architectures for Near-Data Processing
Programming models for distributed and heterogeneous infrastructures, driven by location of the data
Processing/Memory/Storage architectures and microarchitectures for Near-Data Processing
Performance evaluation of Near-Data Processing systems and subsystems
Power-efficiency and reliability analysis and evaluation of Near-Data Processing

Call for Papers:
Two kinds of papers are invited:

Technical papers (4-6 pages) with preliminary results.
Position papers (3 pages maximum) on directions for research and development.

Please submit an electronic copy of your paper (in PDF) in two column format with at least 10pt font. Submission site details will be posted here shortly.

The selected papers will be made available online. However, publication in WoNDP does not preclude later publication at regular conferences or journals.

Important Dates:
Paper submissions due: Monday October 14, 2013
Notification: Monday November 4th, 2013
Final Paper Due: Monday December 2nd, 2013

Organizers:
Jaime Moreno , IBM TJ Watson Research Center
Ravi Nair , IBM TJ Watson Research Center
Rajeev Balasubramonian , University of Utah

Program Committee:
Rajeev Balasubramonian , University of Utah
Jichuan Chang , HP Labs
Jeff Draper , USC/ISI
David Lilja , University of Minnesota
Jaime Moreno , IBM TJ Watson Research Center
Richard Murphy , Micron
Ravi Nair , IBM TJ Watson Research Center