Wednesday, April 28, 2010

Parallel Processing for Imaging Applications

IS&T/SPIE Electronic Imaging is the must attend event for all aspects of electronic imaging, including imaging systems, image processing, image quality, and algorithms. The Symposium Steering Committee, chaired by Sabine Süsstrunk, is starting a new exciting conference on Parallel Processing for Imaging Applications as part of the program track on Image Processing.

The important date is 28 June 2010, when the abstracts are due. You can find the Call for Papers at this easy to remember URL: http://tinyurl.com/ei111ppia.

Here is the aim of the conference:

Papers submitted to this conference should fuse parallel implementation design principles under physical constraints with an understanding of imaging applications.

Imaging translates information into and out of the visual system with today's computation engine of choice: digital electronic systems. While scalar architectures are no longer scaling at historical rates, we see a massive explosion in the total number of connected computation devices and the ways that hardware architectures and software parallel programming environments use these devices to work in concert and in parallel. From the computing cloud to map-reduce programming models and systems to multi-core CPUs to the regular layout of graphics processing units (GPUs) to the increasing capacity of FPGA fabrics, a range of parallel architectures and parallel programming environments are available to designers and researchers to solve computationally complex problems in efficient (and often real-time) imaging applications.

Under physical constraints such as power, speed, and/or cost, the data throughput and degree of data dependence of imaging applications suggest a good match between parallel architectures and imaging applications; similarly, the choice of parallel architectures often reflects the structure of the imaging problem targeted by the application. Thus, the duality of imaging problem definition and parallelism implies that the efficient implementation of parallelism for imaging offers insight into the mind's internal imaging computation. This duality also implies that measures of parallel efficiency can formalize the definition of many imaging problems. This conference explores this duality through new parallel designs for imaging and architectures and design tools to optimize parallelism in imaging algorithms.

The Conference Chairs are John D. Owens, I-Jong Lin, and Yu-Jin Zhang. The members of the Program Committee are Yen-Kuang Chen, Ngai-Man Cheung, Ajay Divakaran, Mei Han, Michael Houston, Wen-Mei Hwu, Christopher R. Johnson, Kurt W. Keutzer, Ron Kimmel, David P. Luebke, Thomas Malzbender, Marilyn C. Wolf, and Robert A. Ulichney.

If in your imaging research you use more than one processing unit, you should definitely consider submitting a paper!