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A Reconfigurable Computing Framework for Multi-scale Cellular Image Processing (2008)

Abstract
Cellular computing architectures represent an important class of computation that are characterized by simple processing elements, local interconnect and massive parallelism. These architectures are a good match for many image and video processing applications and can be substantially accelerated with Reconfigurable Computers. We present a flexible software / hardware framework for design, implementation and automatic synthesis of cellular image processing algorithms. The system provides an extremely flexible set of parallel, pipelined and time-multiplexed components which can be tailored through reconfigurable hardware for particular applications. The most novel aspects of our framework include a highly pipelined architecture for multi-scale cellular image processing as well as support for several different pattern recognition applications. In this paper we will describe the system in detail and present our performance assessments. The system achieved speed-up of at least 100x for computationally expensive sub-problems and 10x for end-to-end applications compared to software implementations. 1

Publication details
Download http://citeseerx.ist.psu.edu/viewdoc/summary?doi=?doi=10.1.1.109.4082
Source http://www.pooka.lanl.gov/content/pooka/green/Publications_files/harpo_draft.pdf
Contributors CiteSeerX
Repository CiteSeerX - Scientific Literature Digital Library and Search Engine (United States)
Type text
Language English
Relation 10.1.1.138.1115, 10.1.1.124.2458, 10.1.1.71.1200, 10.1.1.42.124, 10.1.1.12.4299, 10.1.1.19.4719